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llvm-project/llvm/lib/Transforms/Vectorize/BBVectorize.cpp

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Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
//===- BBVectorize.cpp - A Basic-Block Vectorizer -------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This file implements a basic-block vectorization pass. The algorithm was
// inspired by that used by the Vienna MAP Vectorizor by Franchetti and Kral,
// et al. It works by looking for chains of pairable operations and then
// pairing them.
//
//===----------------------------------------------------------------------===//
#define BBV_NAME "bb-vectorize"
#define DEBUG_TYPE BBV_NAME
#include "llvm/Constants.h"
#include "llvm/DerivedTypes.h"
#include "llvm/Function.h"
#include "llvm/Instructions.h"
#include "llvm/IntrinsicInst.h"
#include "llvm/Intrinsics.h"
#include "llvm/LLVMContext.h"
Teach BBVectorize to combine, when possible, or discard metadata when fusing instructions. The present implementation handles only TBAA and FP metadata, discarding everything else. For debug metadata, the current behavior is maintained (the debug metadata associated with one of the instructions will be kept, discarding that attached to the other). This should address PR 13040. llvm-svn: 158606
2012-06-17 04:34:06 +08:00
#include "llvm/Metadata.h"
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
#include "llvm/Pass.h"
#include "llvm/Type.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/DenseSet.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/Statistic.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/StringExtras.h"
#include "llvm/Analysis/AliasAnalysis.h"
#include "llvm/Analysis/AliasSetTracker.h"
#include "llvm/Analysis/ScalarEvolution.h"
#include "llvm/Analysis/ScalarEvolutionExpressions.h"
#include "llvm/Analysis/ValueTracking.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Support/ValueHandle.h"
#include "llvm/Target/TargetData.h"
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
#include "llvm/Transforms/Utils/Local.h"
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
#include "llvm/Transforms/Vectorize.h"
#include <algorithm>
#include <map>
using namespace llvm;
static cl::opt<unsigned>
ReqChainDepth("bb-vectorize-req-chain-depth", cl::init(6), cl::Hidden,
cl::desc("The required chain depth for vectorization"));
static cl::opt<unsigned>
SearchLimit("bb-vectorize-search-limit", cl::init(400), cl::Hidden,
cl::desc("The maximum search distance for instruction pairs"));
static cl::opt<bool>
SplatBreaksChain("bb-vectorize-splat-breaks-chain", cl::init(false), cl::Hidden,
cl::desc("Replicating one element to a pair breaks the chain"));
static cl::opt<unsigned>
VectorBits("bb-vectorize-vector-bits", cl::init(128), cl::Hidden,
cl::desc("The size of the native vector registers"));
static cl::opt<unsigned>
MaxIter("bb-vectorize-max-iter", cl::init(0), cl::Hidden,
cl::desc("The maximum number of pairing iterations"));
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
static cl::opt<bool>
Pow2LenOnly("bb-vectorize-pow2-len-only", cl::init(false), cl::Hidden,
cl::desc("Don't try to form non-2^n-length vectors"));
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
static cl::opt<unsigned>
MaxInsts("bb-vectorize-max-instr-per-group", cl::init(500), cl::Hidden,
cl::desc("The maximum number of pairable instructions per group"));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
static cl::opt<unsigned>
MaxCandPairsForCycleCheck("bb-vectorize-max-cycle-check-pairs", cl::init(200),
cl::Hidden, cl::desc("The maximum number of candidate pairs with which to use"
" a full cycle check"));
Allow controlling vectorization of boolean values separately from other integer types. These are used as the result of comparisons, and often handled differently from larger integer types. llvm-svn: 159111
2012-06-24 21:28:01 +08:00
static cl::opt<bool>
NoBools("bb-vectorize-no-bools", cl::init(false), cl::Hidden,
cl::desc("Don't try to vectorize boolean (i1) values"));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
static cl::opt<bool>
NoInts("bb-vectorize-no-ints", cl::init(false), cl::Hidden,
cl::desc("Don't try to vectorize integer values"));
static cl::opt<bool>
NoFloats("bb-vectorize-no-floats", cl::init(false), cl::Hidden,
cl::desc("Don't try to vectorize floating-point values"));
Enhance BBVectorize to more-properly handle pointer values and vectorize GEPs. llvm-svn: 154734
2012-04-14 15:32:43 +08:00
static cl::opt<bool>
NoPointers("bb-vectorize-no-pointers", cl::init(false), cl::Hidden,
cl::desc("Don't try to vectorize pointer values"));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
static cl::opt<bool>
NoCasts("bb-vectorize-no-casts", cl::init(false), cl::Hidden,
cl::desc("Don't try to vectorize casting (conversion) operations"));
static cl::opt<bool>
NoMath("bb-vectorize-no-math", cl::init(false), cl::Hidden,
cl::desc("Don't try to vectorize floating-point math intrinsics"));
static cl::opt<bool>
NoFMA("bb-vectorize-no-fma", cl::init(false), cl::Hidden,
cl::desc("Don't try to vectorize the fused-multiply-add intrinsic"));
Add support to BBVectorize for vectorizing selects. llvm-svn: 154700
2012-04-14 04:45:45 +08:00
static cl::opt<bool>
NoSelect("bb-vectorize-no-select", cl::init(false), cl::Hidden,
cl::desc("Don't try to vectorize select instructions"));
Allow BBVectorize to fuse compare instructions. llvm-svn: 159088
2012-06-24 05:52:50 +08:00
static cl::opt<bool>
NoCmp("bb-vectorize-no-cmp", cl::init(false), cl::Hidden,
cl::desc("Don't try to vectorize comparison instructions"));
Enhance BBVectorize to more-properly handle pointer values and vectorize GEPs. llvm-svn: 154734
2012-04-14 15:32:43 +08:00
static cl::opt<bool>
NoGEP("bb-vectorize-no-gep", cl::init(false), cl::Hidden,
cl::desc("Don't try to vectorize getelementptr instructions"));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
static cl::opt<bool>
NoMemOps("bb-vectorize-no-mem-ops", cl::init(false), cl::Hidden,
cl::desc("Don't try to vectorize loads and stores"));
static cl::opt<bool>
AlignedOnly("bb-vectorize-aligned-only", cl::init(false), cl::Hidden,
cl::desc("Only generate aligned loads and stores"));
Boost the effective chain depth of loads and stores. By default, boost the chain depth contribution of loads and stores. This will allow a load/store pair to vectorize even when it would not otherwise be long enough to satisfy the chain depth requirement. llvm-svn: 149761
2012-02-04 12:14:04 +08:00
static cl::opt<bool>
NoMemOpBoost("bb-vectorize-no-mem-op-boost",
cl::init(false), cl::Hidden,
cl::desc("Don't boost the chain-depth contribution of loads and stores"));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
static cl::opt<bool>
FastDep("bb-vectorize-fast-dep", cl::init(false), cl::Hidden,
cl::desc("Use a fast instruction dependency analysis"));
#ifndef NDEBUG
static cl::opt<bool>
DebugInstructionExamination("bb-vectorize-debug-instruction-examination",
cl::init(false), cl::Hidden,
cl::desc("When debugging is enabled, output information on the"
" instruction-examination process"));
static cl::opt<bool>
DebugCandidateSelection("bb-vectorize-debug-candidate-selection",
cl::init(false), cl::Hidden,
cl::desc("When debugging is enabled, output information on the"
" candidate-selection process"));
static cl::opt<bool>
DebugPairSelection("bb-vectorize-debug-pair-selection",
cl::init(false), cl::Hidden,
cl::desc("When debugging is enabled, output information on the"
" pair-selection process"));
static cl::opt<bool>
DebugCycleCheck("bb-vectorize-debug-cycle-check",
cl::init(false), cl::Hidden,
cl::desc("When debugging is enabled, output information on the"
" cycle-checking process"));
#endif
STATISTIC(NumFusedOps, "Number of operations fused by bb-vectorize");
namespace {
struct BBVectorize : public BasicBlockPass {
static char ID; // Pass identification, replacement for typeid
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
BBVectorize: Add the const modifier to the VectorizeConfig because we won't modify it. llvm-svn: 154098
2012-04-06 00:07:49 +08:00
const VectorizeConfig Config;
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
BBVectorize(const VectorizeConfig &C = VectorizeConfig())
: BasicBlockPass(ID), Config(C) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
initializeBBVectorizePass(*PassRegistry::getPassRegistry());
}
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
BBVectorize(Pass *P, const VectorizeConfig &C)
: BasicBlockPass(ID), Config(C) {
Add the function "vectorizeBasicBlock" which allow users vectorize a BasicBlock in other passes, e.g. we can call vectorizeBasicBlock in the loop unroll pass right after the loop is unrolled. llvm-svn: 154089
2012-04-05 16:05:16 +08:00
AA = &P->getAnalysis<AliasAnalysis>();
SE = &P->getAnalysis<ScalarEvolution>();
TD = P->getAnalysisIfAvailable<TargetData>();
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
typedef std::pair<Value *, Value *> ValuePair;
typedef std::pair<ValuePair, size_t> ValuePairWithDepth;
typedef std::pair<ValuePair, ValuePair> VPPair; // A ValuePair pair
typedef std::pair<std::multimap<Value *, Value *>::iterator,
std::multimap<Value *, Value *>::iterator> VPIteratorPair;
typedef std::pair<std::multimap<ValuePair, ValuePair>::iterator,
std::multimap<ValuePair, ValuePair>::iterator>
VPPIteratorPair;
AliasAnalysis *AA;
ScalarEvolution *SE;
TargetData *TD;
// FIXME: const correct?
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
bool vectorizePairs(BasicBlock &BB, bool NonPow2Len = false);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
bool getCandidatePairs(BasicBlock &BB,
BasicBlock::iterator &Start,
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
std::multimap<Value *, Value *> &CandidatePairs,
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
std::vector<Value *> &PairableInsts, bool NonPow2Len);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
void computeConnectedPairs(std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs);
void buildDepMap(BasicBlock &BB,
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
DenseSet<ValuePair> &PairableInstUsers);
void choosePairs(std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs,
DenseSet<ValuePair> &PairableInstUsers,
DenseMap<Value *, Value *>& ChosenPairs);
void fuseChosenPairs(BasicBlock &BB,
std::vector<Value *> &PairableInsts,
DenseMap<Value *, Value *>& ChosenPairs);
bool isInstVectorizable(Instruction *I, bool &IsSimpleLoadStore);
bool areInstsCompatible(Instruction *I, Instruction *J,
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
bool IsSimpleLoadStore, bool NonPow2Len);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
bool trackUsesOfI(DenseSet<Value *> &Users,
AliasSetTracker &WriteSet, Instruction *I,
Instruction *J, bool UpdateUsers = true,
std::multimap<Value *, Value *> *LoadMoveSet = 0);
fix indentation llvm-svn: 149857
2012-02-06 13:29:32 +08:00
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
void computePairsConnectedTo(
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs,
ValuePair P);
bool pairsConflict(ValuePair P, ValuePair Q,
DenseSet<ValuePair> &PairableInstUsers,
std::multimap<ValuePair, ValuePair> *PairableInstUserMap = 0);
bool pairWillFormCycle(ValuePair P,
std::multimap<ValuePair, ValuePair> &PairableInstUsers,
DenseSet<ValuePair> &CurrentPairs);
void pruneTreeFor(
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs,
DenseSet<ValuePair> &PairableInstUsers,
std::multimap<ValuePair, ValuePair> &PairableInstUserMap,
DenseMap<Value *, Value *> &ChosenPairs,
DenseMap<ValuePair, size_t> &Tree,
DenseSet<ValuePair> &PrunedTree, ValuePair J,
bool UseCycleCheck);
void buildInitialTreeFor(
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs,
DenseSet<ValuePair> &PairableInstUsers,
DenseMap<Value *, Value *> &ChosenPairs,
DenseMap<ValuePair, size_t> &Tree, ValuePair J);
void findBestTreeFor(
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs,
DenseSet<ValuePair> &PairableInstUsers,
std::multimap<ValuePair, ValuePair> &PairableInstUserMap,
DenseMap<Value *, Value *> &ChosenPairs,
DenseSet<ValuePair> &BestTree, size_t &BestMaxDepth,
size_t &BestEffSize, VPIteratorPair ChoiceRange,
bool UseCycleCheck);
Value *getReplacementPointerInput(LLVMContext& Context, Instruction *I,
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
Instruction *J, unsigned o, bool FlipMemInputs);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
void fillNewShuffleMask(LLVMContext& Context, Instruction *J,
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
unsigned MaskOffset, unsigned NumInElem,
unsigned NumInElem1, unsigned IdxOffset,
std::vector<Constant*> &Mask);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Value *getReplacementShuffleMask(LLVMContext& Context, Instruction *I,
Instruction *J);
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
bool expandIEChain(LLVMContext& Context, Instruction *I, Instruction *J,
unsigned o, Value *&LOp, unsigned numElemL,
Type *ArgTypeL, Type *ArgTypeR,
unsigned IdxOff = 0);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Value *getReplacementInput(LLVMContext& Context, Instruction *I,
Instruction *J, unsigned o, bool FlipMemInputs);
void getReplacementInputsForPair(LLVMContext& Context, Instruction *I,
Instruction *J, SmallVector<Value *, 3> &ReplacedOperands,
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
bool FlipMemInputs);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
void replaceOutputsOfPair(LLVMContext& Context, Instruction *I,
Instruction *J, Instruction *K,
Instruction *&InsertionPt, Instruction *&K1,
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
Instruction *&K2, bool FlipMemInputs);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
void collectPairLoadMoveSet(BasicBlock &BB,
DenseMap<Value *, Value *> &ChosenPairs,
std::multimap<Value *, Value *> &LoadMoveSet,
Instruction *I);
void collectLoadMoveSet(BasicBlock &BB,
std::vector<Value *> &PairableInsts,
DenseMap<Value *, Value *> &ChosenPairs,
std::multimap<Value *, Value *> &LoadMoveSet);
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
void collectPtrInfo(std::vector<Value *> &PairableInsts,
DenseMap<Value *, Value *> &ChosenPairs,
DenseSet<Value *> &LowPtrInsts);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
bool canMoveUsesOfIAfterJ(BasicBlock &BB,
std::multimap<Value *, Value *> &LoadMoveSet,
Instruction *I, Instruction *J);
void moveUsesOfIAfterJ(BasicBlock &BB,
std::multimap<Value *, Value *> &LoadMoveSet,
Instruction *&InsertionPt,
Instruction *I, Instruction *J);
Teach BBVectorize to combine, when possible, or discard metadata when fusing instructions. The present implementation handles only TBAA and FP metadata, discarding everything else. For debug metadata, the current behavior is maintained (the debug metadata associated with one of the instructions will be kept, discarding that attached to the other). This should address PR 13040. llvm-svn: 158606
2012-06-17 04:34:06 +08:00
void combineMetadata(Instruction *K, const Instruction *J);
Add the function "vectorizeBasicBlock" which allow users vectorize a BasicBlock in other passes, e.g. we can call vectorizeBasicBlock in the loop unroll pass right after the loop is unrolled. llvm-svn: 154089
2012-04-05 16:05:16 +08:00
bool vectorizeBB(BasicBlock &BB) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
bool changed = false;
// Iterate a sufficient number of times to merge types of size 1 bit,
// then 2 bits, then 4, etc. up to half of the target vector width of the
// target vector register.
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
unsigned n = 1;
for (unsigned v = 2;
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
v <= Config.VectorBits && (!Config.MaxIter || n <= Config.MaxIter);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
v *= 2, ++n) {
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
DEBUG(dbgs() << "BBV: fusing loop #" << n <<
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
" for " << BB.getName() << " in " <<
BB.getParent()->getName() << "...\n");
if (vectorizePairs(BB))
changed = true;
else
break;
}
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
if (changed && !Pow2LenOnly) {
++n;
for (; !Config.MaxIter || n <= Config.MaxIter; ++n) {
DEBUG(dbgs() << "BBV: fusing for non-2^n-length vectors loop #: " <<
n << " for " << BB.getName() << " in " <<
BB.getParent()->getName() << "...\n");
if (!vectorizePairs(BB, true)) break;
}
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
DEBUG(dbgs() << "BBV: done!\n");
return changed;
}
Add the function "vectorizeBasicBlock" which allow users vectorize a BasicBlock in other passes, e.g. we can call vectorizeBasicBlock in the loop unroll pass right after the loop is unrolled. llvm-svn: 154089
2012-04-05 16:05:16 +08:00
virtual bool runOnBasicBlock(BasicBlock &BB) {
AA = &getAnalysis<AliasAnalysis>();
SE = &getAnalysis<ScalarEvolution>();
TD = getAnalysisIfAvailable<TargetData>();
return vectorizeBB(BB);
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
virtual void getAnalysisUsage(AnalysisUsage &AU) const {
BasicBlockPass::getAnalysisUsage(AU);
AU.addRequired<AliasAnalysis>();
AU.addRequired<ScalarEvolution>();
AU.addPreserved<AliasAnalysis>();
AU.addPreserved<ScalarEvolution>();
A few of the changes suggested in code review (by Nick Lewycky) llvm-svn: 149472
2012-02-01 13:51:45 +08:00
AU.setPreservesCFG();
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
static inline VectorType *getVecTypeForPair(Type *ElemTy, Type *Elem2Ty) {
assert(ElemTy->getScalarType() == Elem2Ty->getScalarType() &&
"Cannot form vector from incompatible scalar types");
Type *STy = ElemTy->getScalarType();
unsigned numElem;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
if (VectorType *VTy = dyn_cast<VectorType>(ElemTy)) {
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
numElem = VTy->getNumElements();
} else {
numElem = 1;
}
if (VectorType *VTy = dyn_cast<VectorType>(Elem2Ty)) {
numElem += VTy->getNumElements();
} else {
numElem += 1;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
A few of the changes suggested in code review (by Nick Lewycky) llvm-svn: 149472
2012-02-01 13:51:45 +08:00
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
return VectorType::get(STy, numElem);
}
static inline void getInstructionTypes(Instruction *I,
Type *&T1, Type *&T2) {
if (isa<StoreInst>(I)) {
// For stores, it is the value type, not the pointer type that matters
// because the value is what will come from a vector register.
Value *IVal = cast<StoreInst>(I)->getValueOperand();
T1 = IVal->getType();
} else {
T1 = I->getType();
}
if (I->isCast())
T2 = cast<CastInst>(I)->getSrcTy();
else
T2 = T1;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
// Returns the weight associated with the provided value. A chain of
// candidate pairs has a length given by the sum of the weights of its
// members (one weight per pair; the weight of each member of the pair
// is assumed to be the same). This length is then compared to the
// chain-length threshold to determine if a given chain is significant
// enough to be vectorized. The length is also used in comparing
// candidate chains where longer chains are considered to be better.
// Note: when this function returns 0, the resulting instructions are
// not actually fused.
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
inline size_t getDepthFactor(Value *V) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// InsertElement and ExtractElement have a depth factor of zero. This is
// for two reasons: First, they cannot be usefully fused. Second, because
// the pass generates a lot of these, they can confuse the simple metric
// used to compare the trees in the next iteration. Thus, giving them a
// weight of zero allows the pass to essentially ignore them in
// subsequent iterations when looking for vectorization opportunities
// while still tracking dependency chains that flow through those
// instructions.
if (isa<InsertElementInst>(V) || isa<ExtractElementInst>(V))
return 0;
Boost the effective chain depth of loads and stores. By default, boost the chain depth contribution of loads and stores. This will allow a load/store pair to vectorize even when it would not otherwise be long enough to satisfy the chain depth requirement. llvm-svn: 149761
2012-02-04 12:14:04 +08:00
// Give a load or store half of the required depth so that load/store
// pairs will vectorize.
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
if (!Config.NoMemOpBoost && (isa<LoadInst>(V) || isa<StoreInst>(V)))
return Config.ReqChainDepth/2;
Boost the effective chain depth of loads and stores. By default, boost the chain depth contribution of loads and stores. This will allow a load/store pair to vectorize even when it would not otherwise be long enough to satisfy the chain depth requirement. llvm-svn: 149761
2012-02-04 12:14:04 +08:00
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return 1;
}
// This determines the relative offset of two loads or stores, returning
// true if the offset could be determined to be some constant value.
// For example, if OffsetInElmts == 1, then J accesses the memory directly
// after I; if OffsetInElmts == -1 then I accesses the memory
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
// directly after J.
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
bool getPairPtrInfo(Instruction *I, Instruction *J,
Value *&IPtr, Value *&JPtr, unsigned &IAlignment, unsigned &JAlignment,
int64_t &OffsetInElmts) {
OffsetInElmts = 0;
if (isa<LoadInst>(I)) {
IPtr = cast<LoadInst>(I)->getPointerOperand();
JPtr = cast<LoadInst>(J)->getPointerOperand();
IAlignment = cast<LoadInst>(I)->getAlignment();
JAlignment = cast<LoadInst>(J)->getAlignment();
} else {
IPtr = cast<StoreInst>(I)->getPointerOperand();
JPtr = cast<StoreInst>(J)->getPointerOperand();
IAlignment = cast<StoreInst>(I)->getAlignment();
JAlignment = cast<StoreInst>(J)->getAlignment();
}
const SCEV *IPtrSCEV = SE->getSCEV(IPtr);
const SCEV *JPtrSCEV = SE->getSCEV(JPtr);
// If this is a trivial offset, then we'll get something like
// 1*sizeof(type). With target data, which we need anyway, this will get
// constant folded into a number.
const SCEV *OffsetSCEV = SE->getMinusSCEV(JPtrSCEV, IPtrSCEV);
if (const SCEVConstant *ConstOffSCEV =
dyn_cast<SCEVConstant>(OffsetSCEV)) {
ConstantInt *IntOff = ConstOffSCEV->getValue();
int64_t Offset = IntOff->getSExtValue();
Type *VTy = cast<PointerType>(IPtr->getType())->getElementType();
int64_t VTyTSS = (int64_t) TD->getTypeStoreSize(VTy);
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Type *VTy2 = cast<PointerType>(JPtr->getType())->getElementType();
if (VTy != VTy2 && Offset < 0) {
int64_t VTy2TSS = (int64_t) TD->getTypeStoreSize(VTy2);
OffsetInElmts = Offset/VTy2TSS;
return (abs64(Offset) % VTy2TSS) == 0;
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
OffsetInElmts = Offset/VTyTSS;
return (abs64(Offset) % VTyTSS) == 0;
}
return false;
}
// Returns true if the provided CallInst represents an intrinsic that can
// be vectorized.
bool isVectorizableIntrinsic(CallInst* I) {
Function *F = I->getCalledFunction();
if (!F) return false;
unsigned IID = F->getIntrinsicID();
if (!IID) return false;
switch(IID) {
default:
return false;
case Intrinsic::sqrt:
case Intrinsic::powi:
case Intrinsic::sin:
case Intrinsic::cos:
case Intrinsic::log:
case Intrinsic::log2:
case Intrinsic::log10:
case Intrinsic::exp:
case Intrinsic::exp2:
case Intrinsic::pow:
Refactor: Use positive field names in VectorizeConfig. llvm-svn: 154249
2012-04-07 11:56:23 +08:00
return Config.VectorizeMath;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
case Intrinsic::fma:
Refactor: Use positive field names in VectorizeConfig. llvm-svn: 154249
2012-04-07 11:56:23 +08:00
return Config.VectorizeFMA;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
}
// Returns true if J is the second element in some pair referenced by
// some multimap pair iterator pair.
template <typename V>
bool isSecondInIteratorPair(V J, std::pair<
typename std::multimap<V, V>::iterator,
typename std::multimap<V, V>::iterator> PairRange) {
for (typename std::multimap<V, V>::iterator K = PairRange.first;
K != PairRange.second; ++K)
if (K->second == J) return true;
return false;
}
};
// This function implements one vectorization iteration on the provided
// basic block. It returns true if the block is changed.
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
bool BBVectorize::vectorizePairs(BasicBlock &BB, bool NonPow2Len) {
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
bool ShouldContinue;
BasicBlock::iterator Start = BB.getFirstInsertionPt();
std::vector<Value *> AllPairableInsts;
DenseMap<Value *, Value *> AllChosenPairs;
do {
std::vector<Value *> PairableInsts;
std::multimap<Value *, Value *> CandidatePairs;
ShouldContinue = getCandidatePairs(BB, Start, CandidatePairs,
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
PairableInsts, NonPow2Len);
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
if (PairableInsts.empty()) continue;
remove spaces on empty lines llvm-svn: 152034
2012-03-06 01:39:45 +08:00
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
// Now we have a map of all of the pairable instructions and we need to
// select the best possible pairing. A good pairing is one such that the
// users of the pair are also paired. This defines a (directed) forest
// over the pairs such that two pairs are connected iff the second pair
// uses the first.
remove spaces on empty lines llvm-svn: 152034
2012-03-06 01:39:45 +08:00
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
// Note that it only matters that both members of the second pair use some
// element of the first pair (to allow for splatting).
remove spaces on empty lines llvm-svn: 152034
2012-03-06 01:39:45 +08:00
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
std::multimap<ValuePair, ValuePair> ConnectedPairs;
computeConnectedPairs(CandidatePairs, PairableInsts, ConnectedPairs);
if (ConnectedPairs.empty()) continue;
remove spaces on empty lines llvm-svn: 152034
2012-03-06 01:39:45 +08:00
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
// Build the pairable-instruction dependency map
DenseSet<ValuePair> PairableInstUsers;
buildDepMap(BB, CandidatePairs, PairableInsts, PairableInstUsers);
remove spaces on empty lines llvm-svn: 152034
2012-03-06 01:39:45 +08:00
Minor changes from review. As suggested by Nick Lewycky, the tree traversal queues have been changed to SmallVectors and the associated loops have been rotated. Also, an 80-col violation was fixed. llvm-svn: 149607
2012-02-03 01:29:39 +08:00
// There is now a graph of the connected pairs. For each variable, pick
// the pairing with the largest tree meeting the depth requirement on at
// least one branch. Then select all pairings that are part of that tree
// and remove them from the list of available pairings and pairable
// variables.
remove spaces on empty lines llvm-svn: 152034
2012-03-06 01:39:45 +08:00
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
DenseMap<Value *, Value *> ChosenPairs;
choosePairs(CandidatePairs, PairableInsts, ConnectedPairs,
PairableInstUsers, ChosenPairs);
remove spaces on empty lines llvm-svn: 152034
2012-03-06 01:39:45 +08:00
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
if (ChosenPairs.empty()) continue;
AllPairableInsts.insert(AllPairableInsts.end(), PairableInsts.begin(),
PairableInsts.end());
AllChosenPairs.insert(ChosenPairs.begin(), ChosenPairs.end());
} while (ShouldContinue);
if (AllChosenPairs.empty()) return false;
NumFusedOps += AllChosenPairs.size();
remove spaces on empty lines llvm-svn: 152034
2012-03-06 01:39:45 +08:00
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// A set of pairs has now been selected. It is now necessary to replace the
// paired instructions with vector instructions. For this procedure each
fix typos llvm-svn: 152035
2012-03-06 01:39:47 +08:00
// operand must be replaced with a vector operand. This vector is formed
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// by using build_vector on the old operands. The replaced values are then
// replaced with a vector_extract on the result. Subsequent optimization
// passes should coalesce the build/extract combinations.
remove spaces on empty lines llvm-svn: 152034
2012-03-06 01:39:45 +08:00
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
fuseChosenPairs(BB, AllPairableInsts, AllChosenPairs);
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
// It is important to cleanup here so that future iterations of this
// function have less work to do.
(void) SimplifyInstructionsInBlock(&BB, TD);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return true;
}
// This function returns true if the provided instruction is capable of being
// fused into a vector instruction. This determination is based only on the
// type and other attributes of the instruction.
bool BBVectorize::isInstVectorizable(Instruction *I,
bool &IsSimpleLoadStore) {
IsSimpleLoadStore = false;
if (CallInst *C = dyn_cast<CallInst>(I)) {
if (!isVectorizableIntrinsic(C))
return false;
} else if (LoadInst *L = dyn_cast<LoadInst>(I)) {
// Vectorize simple loads if possbile:
IsSimpleLoadStore = L->isSimple();
Refactor: Use positive field names in VectorizeConfig. llvm-svn: 154249
2012-04-07 11:56:23 +08:00
if (!IsSimpleLoadStore || !Config.VectorizeMemOps)
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return false;
} else if (StoreInst *S = dyn_cast<StoreInst>(I)) {
// Vectorize simple stores if possbile:
IsSimpleLoadStore = S->isSimple();
Refactor: Use positive field names in VectorizeConfig. llvm-svn: 154249
2012-04-07 11:56:23 +08:00
if (!IsSimpleLoadStore || !Config.VectorizeMemOps)
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return false;
} else if (CastInst *C = dyn_cast<CastInst>(I)) {
// We can vectorize casts, but not casts of pointer types, etc.
Refactor: Use positive field names in VectorizeConfig. llvm-svn: 154249
2012-04-07 11:56:23 +08:00
if (!Config.VectorizeCasts)
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return false;
Type *SrcTy = C->getSrcTy();
Enhance BBVectorize to more-properly handle pointer values and vectorize GEPs. llvm-svn: 154734
2012-04-14 15:32:43 +08:00
if (!SrcTy->isSingleValueType())
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return false;
Type *DestTy = C->getDestTy();
Enhance BBVectorize to more-properly handle pointer values and vectorize GEPs. llvm-svn: 154734
2012-04-14 15:32:43 +08:00
if (!DestTy->isSingleValueType())
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return false;
Add support to BBVectorize for vectorizing selects. llvm-svn: 154700
2012-04-14 04:45:45 +08:00
} else if (isa<SelectInst>(I)) {
if (!Config.VectorizeSelect)
return false;
Allow BBVectorize to fuse compare instructions. llvm-svn: 159088
2012-06-24 05:52:50 +08:00
} else if (isa<CmpInst>(I)) {
if (!Config.VectorizeCmp)
return false;
Enhance BBVectorize to more-properly handle pointer values and vectorize GEPs. llvm-svn: 154734
2012-04-14 15:32:43 +08:00
} else if (GetElementPtrInst *G = dyn_cast<GetElementPtrInst>(I)) {
if (!Config.VectorizeGEP)
return false;
// Currently, vector GEPs exist only with one index.
if (G->getNumIndices() != 1)
return false;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
} else if (!(I->isBinaryOp() || isa<ShuffleVectorInst>(I) ||
isa<ExtractElementInst>(I) || isa<InsertElementInst>(I))) {
return false;
}
// We can't vectorize memory operations without target data
if (TD == 0 && IsSimpleLoadStore)
return false;
Type *T1, *T2;
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
getInstructionTypes(I, T1, T2);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// Not every type can be vectorized...
if (!(VectorType::isValidElementType(T1) || T1->isVectorTy()) ||
!(VectorType::isValidElementType(T2) || T2->isVectorTy()))
return false;
Allow controlling vectorization of boolean values separately from other integer types. These are used as the result of comparisons, and often handled differently from larger integer types. llvm-svn: 159111
2012-06-24 21:28:01 +08:00
if (T1->getScalarSizeInBits() == 1 && T2->getScalarSizeInBits() == 1) {
if (!Config.VectorizeBools)
return false;
} else {
if (!Config.VectorizeInts
&& (T1->isIntOrIntVectorTy() || T2->isIntOrIntVectorTy()))
return false;
}
Refactor: Use positive field names in VectorizeConfig. llvm-svn: 154249
2012-04-07 11:56:23 +08:00
if (!Config.VectorizeFloats
&& (T1->isFPOrFPVectorTy() || T2->isFPOrFPVectorTy()))
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return false;
Don't vectorize target-specific types (ppc_fp128, x86_fp80, etc.). Target specific types should not be vectorized. As a practical matter, these types are already register matched (at least in the x86 case), and codegen does not always work correctly (at least in the ppc case, and this is not worth fixing because ppc_fp128 is currently broken and will probably go away soon). llvm-svn: 155729
2012-04-28 03:34:00 +08:00
// Don't vectorize target-specific types.
if (T1->isX86_FP80Ty() || T1->isPPC_FP128Ty() || T1->isX86_MMXTy())
return false;
if (T2->isX86_FP80Ty() || T2->isPPC_FP128Ty() || T2->isX86_MMXTy())
return false;
Fix style violation in BBVectorize (pointed out by Bill Wendling) llvm-svn: 154810
2012-04-16 20:39:17 +08:00
if ((!Config.VectorizePointers || TD == 0) &&
(T1->getScalarType()->isPointerTy() ||
T2->getScalarType()->isPointerTy()))
Enhance BBVectorize to more-properly handle pointer values and vectorize GEPs. llvm-svn: 154734
2012-04-14 15:32:43 +08:00
return false;
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
if (T1->getPrimitiveSizeInBits() >= Config.VectorBits ||
T2->getPrimitiveSizeInBits() >= Config.VectorBits)
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return false;
return true;
}
// This function returns true if the two provided instructions are compatible
// (meaning that they can be fused into a vector instruction). This assumes
// that I has already been determined to be vectorizable and that J is not
// in the use tree of I.
bool BBVectorize::areInstsCompatible(Instruction *I, Instruction *J,
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
bool IsSimpleLoadStore, bool NonPow2Len) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
DEBUG(if (DebugInstructionExamination) dbgs() << "BBV: looking at " << *I <<
" <-> " << *J << "\n");
// Loads and stores can be merged if they have different alignments,
// but are otherwise the same.
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
if (!J->isSameOperationAs(I, Instruction::CompareIgnoringAlignment |
(NonPow2Len ? Instruction::CompareUsingScalarTypes : 0)))
return false;
Type *IT1, *IT2, *JT1, *JT2;
getInstructionTypes(I, IT1, IT2);
getInstructionTypes(J, JT1, JT2);
unsigned MaxTypeBits = std::max(
IT1->getPrimitiveSizeInBits() + JT1->getPrimitiveSizeInBits(),
IT2->getPrimitiveSizeInBits() + JT2->getPrimitiveSizeInBits());
if (MaxTypeBits > Config.VectorBits)
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return false;
Refactor operation equivalence checking in BBVectorize by extending Instruction::isSameOperationAs. Maintaining this kind of checking in different places is dangerous, extending Instruction::isSameOperationAs consolidates this logic into one place. Here I've added an optional flags parameter and two flags that are important for vectorization: CompareIgnoringAlignment and CompareUsingScalarTypes. llvm-svn: 159329
2012-06-28 13:42:26 +08:00
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// FIXME: handle addsub-type operations!
if (IsSimpleLoadStore) {
Value *IPtr, *JPtr;
unsigned IAlignment, JAlignment;
int64_t OffsetInElmts = 0;
if (getPairPtrInfo(I, J, IPtr, JPtr, IAlignment, JAlignment,
OffsetInElmts) && abs64(OffsetInElmts) == 1) {
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
if (Config.AlignedOnly) {
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Type *aTypeI = isa<StoreInst>(I) ?
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
cast<StoreInst>(I)->getValueOperand()->getType() : I->getType();
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Type *aTypeJ = isa<StoreInst>(J) ?
cast<StoreInst>(J)->getValueOperand()->getType() : J->getType();
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// An aligned load or store is possible only if the instruction
// with the lower offset has an alignment suitable for the
// vector type.
fix indentation llvm-svn: 149857
2012-02-06 13:29:32 +08:00
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
unsigned BottomAlignment = IAlignment;
if (OffsetInElmts < 0) BottomAlignment = JAlignment;
fix indentation llvm-svn: 149857
2012-02-06 13:29:32 +08:00
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Type *VType = getVecTypeForPair(aTypeI, aTypeJ);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
unsigned VecAlignment = TD->getPrefTypeAlignment(VType);
if (BottomAlignment < VecAlignment)
return false;
}
} else {
return false;
}
}
Correctly vectorize powi. The powi intrinsic requires special handling because it always takes a single integer power regardless of the result type. As a result, we can vectorize only if the powers are equal. Fixes PR12364. llvm-svn: 153797
2012-03-31 11:38:40 +08:00
// The powi intrinsic is special because only the first argument is
// vectorized, the second arguments must be equal.
CallInst *CI = dyn_cast<CallInst>(I);
Function *FI;
if (CI && (FI = CI->getCalledFunction()) &&
FI->getIntrinsicID() == Intrinsic::powi) {
Value *A1I = CI->getArgOperand(1),
*A1J = cast<CallInst>(J)->getArgOperand(1);
const SCEV *A1ISCEV = SE->getSCEV(A1I),
*A1JSCEV = SE->getSCEV(A1J);
return (A1ISCEV == A1JSCEV);
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return true;
}
// Figure out whether or not J uses I and update the users and write-set
// structures associated with I. Specifically, Users represents the set of
// instructions that depend on I. WriteSet represents the set
// of memory locations that are dependent on I. If UpdateUsers is true,
// and J uses I, then Users is updated to contain J and WriteSet is updated
// to contain any memory locations to which J writes. The function returns
// true if J uses I. By default, alias analysis is used to determine
// whether J reads from memory that overlaps with a location in WriteSet.
// If LoadMoveSet is not null, then it is a previously-computed multimap
// where the key is the memory-based user instruction and the value is
// the instruction to be compared with I. So, if LoadMoveSet is provided,
// then the alias analysis is not used. This is necessary because this
// function is called during the process of moving instructions during
// vectorization and the results of the alias analysis are not stable during
// that process.
bool BBVectorize::trackUsesOfI(DenseSet<Value *> &Users,
AliasSetTracker &WriteSet, Instruction *I,
Instruction *J, bool UpdateUsers,
std::multimap<Value *, Value *> *LoadMoveSet) {
bool UsesI = false;
// This instruction may already be marked as a user due, for example, to
// being a member of a selected pair.
if (Users.count(J))
UsesI = true;
if (!UsesI)
A few of the changes suggested in code review (by Nick Lewycky) llvm-svn: 149472
2012-02-01 13:51:45 +08:00
for (User::op_iterator JU = J->op_begin(), JE = J->op_end();
JU != JE; ++JU) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Value *V = *JU;
if (I == V || Users.count(V)) {
UsesI = true;
break;
}
}
if (!UsesI && J->mayReadFromMemory()) {
if (LoadMoveSet) {
VPIteratorPair JPairRange = LoadMoveSet->equal_range(J);
UsesI = isSecondInIteratorPair<Value*>(I, JPairRange);
} else {
for (AliasSetTracker::iterator W = WriteSet.begin(),
WE = WriteSet.end(); W != WE; ++W) {
Update BBVectorize to use aliasesUnknownInst. This allows BBVectorize to check the "unknown instruction" list in the alias sets. This is important to prevent instruction fusing from reordering function calls. Resolves PR11920. llvm-svn: 150250
2012-02-10 23:52:40 +08:00
if (W->aliasesUnknownInst(J, *AA)) {
UsesI = true;
break;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
}
}
}
if (UsesI && UpdateUsers) {
if (J->mayWriteToMemory()) WriteSet.add(J);
Users.insert(J);
}
return UsesI;
}
// This function iterates over all instruction pairs in the provided
// basic block and collects all candidate pairs for vectorization.
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
bool BBVectorize::getCandidatePairs(BasicBlock &BB,
BasicBlock::iterator &Start,
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
std::multimap<Value *, Value *> &CandidatePairs,
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
std::vector<Value *> &PairableInsts, bool NonPow2Len) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
BasicBlock::iterator E = BB.end();
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
if (Start == E) return false;
bool ShouldContinue = false, IAfterStart = false;
for (BasicBlock::iterator I = Start++; I != E; ++I) {
if (I == Start) IAfterStart = true;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
bool IsSimpleLoadStore;
if (!isInstVectorizable(I, IsSimpleLoadStore)) continue;
// Look for an instruction with which to pair instruction *I...
DenseSet<Value *> Users;
AliasSetTracker WriteSet(*AA);
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
bool JAfterStart = IAfterStart;
BasicBlock::iterator J = llvm::next(I);
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
for (unsigned ss = 0; J != E && ss <= Config.SearchLimit; ++J, ++ss) {
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
if (J == Start) JAfterStart = true;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// Determine if J uses I, if so, exit the loop.
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
bool UsesI = trackUsesOfI(Users, WriteSet, I, J, !Config.FastDep);
if (Config.FastDep) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// Note: For this heuristic to be effective, independent operations
// must tend to be intermixed. This is likely to be true from some
// kinds of grouped loop unrolling (but not the generic LLVM pass),
// but otherwise may require some kind of reordering pass.
// When using fast dependency analysis,
// stop searching after first use:
if (UsesI) break;
} else {
if (UsesI) continue;
}
// J does not use I, and comes before the first use of I, so it can be
// merged with I if the instructions are compatible.
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
if (!areInstsCompatible(I, J, IsSimpleLoadStore, NonPow2Len)) continue;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// J is a candidate for merging with I.
if (!PairableInsts.size() ||
PairableInsts[PairableInsts.size()-1] != I) {
PairableInsts.push_back(I);
}
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
CandidatePairs.insert(ValuePair(I, J));
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
// The next call to this function must start after the last instruction
// selected during this invocation.
if (JAfterStart) {
Start = llvm::next(J);
IAfterStart = JAfterStart = false;
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
DEBUG(if (DebugCandidateSelection) dbgs() << "BBV: candidate pair "
<< *I << " <-> " << *J << "\n");
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
// If we have already found too many pairs, break here and this function
// will be called again starting after the last instruction selected
// during this invocation.
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
if (PairableInsts.size() >= Config.MaxInsts) {
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
ShouldContinue = true;
break;
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
if (ShouldContinue)
break;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
DEBUG(dbgs() << "BBV: found " << PairableInsts.size()
<< " instructions with candidate pairs\n");
Vectorize long blocks in groups. Long basic blocks with many candidate pairs (such as in the SHA implementation in Perl 5.14; thanks to Roman Divacky for the example) used to take an unacceptably-long time to compile. Instead, break long blocks into groups so that no group has too many candidate pairs. llvm-svn: 149595
2012-02-02 14:14:56 +08:00
return ShouldContinue;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
// Finds candidate pairs connected to the pair P = <PI, PJ>. This means that
// it looks for pairs such that both members have an input which is an
// output of PI or PJ.
void BBVectorize::computePairsConnectedTo(
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs,
ValuePair P) {
Fix an error in BBVectorize important for vectorizing pointer types. When vectorizing pointer types it is important to realize that potential pairs cannot be connected via the address pointer argument of a load or store. This is because even after vectorization, the address is still a scalar because the address of the higher half of the pair is implicit from the address of the lower half (it need not be, and should not be, explicitly computed). llvm-svn: 154735
2012-04-14 15:32:50 +08:00
StoreInst *SI, *SJ;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// For each possible pairing for this variable, look at the uses of
// the first value...
for (Value::use_iterator I = P.first->use_begin(),
E = P.first->use_end(); I != E; ++I) {
Fix an error in BBVectorize important for vectorizing pointer types. When vectorizing pointer types it is important to realize that potential pairs cannot be connected via the address pointer argument of a load or store. This is because even after vectorization, the address is still a scalar because the address of the higher half of the pair is implicit from the address of the lower half (it need not be, and should not be, explicitly computed). llvm-svn: 154735
2012-04-14 15:32:50 +08:00
if (isa<LoadInst>(*I)) {
// A pair cannot be connected to a load because the load only takes one
// operand (the address) and it is a scalar even after vectorization.
continue;
} else if ((SI = dyn_cast<StoreInst>(*I)) &&
P.first == SI->getPointerOperand()) {
// Similarly, a pair cannot be connected to a store through its
// pointer operand.
continue;
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
VPIteratorPair IPairRange = CandidatePairs.equal_range(*I);
// For each use of the first variable, look for uses of the second
// variable...
for (Value::use_iterator J = P.second->use_begin(),
E2 = P.second->use_end(); J != E2; ++J) {
Fix an error in BBVectorize important for vectorizing pointer types. When vectorizing pointer types it is important to realize that potential pairs cannot be connected via the address pointer argument of a load or store. This is because even after vectorization, the address is still a scalar because the address of the higher half of the pair is implicit from the address of the lower half (it need not be, and should not be, explicitly computed). llvm-svn: 154735
2012-04-14 15:32:50 +08:00
if ((SJ = dyn_cast<StoreInst>(*J)) &&
P.second == SJ->getPointerOperand())
continue;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
VPIteratorPair JPairRange = CandidatePairs.equal_range(*J);
// Look for <I, J>:
if (isSecondInIteratorPair<Value*>(*J, IPairRange))
ConnectedPairs.insert(VPPair(P, ValuePair(*I, *J)));
// Look for <J, I>:
if (isSecondInIteratorPair<Value*>(*I, JPairRange))
ConnectedPairs.insert(VPPair(P, ValuePair(*J, *I)));
}
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
if (Config.SplatBreaksChain) continue;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// Look for cases where just the first value in the pair is used by
// both members of another pair (splatting).
for (Value::use_iterator J = P.first->use_begin(); J != E; ++J) {
Fix an error in BBVectorize important for vectorizing pointer types. When vectorizing pointer types it is important to realize that potential pairs cannot be connected via the address pointer argument of a load or store. This is because even after vectorization, the address is still a scalar because the address of the higher half of the pair is implicit from the address of the lower half (it need not be, and should not be, explicitly computed). llvm-svn: 154735
2012-04-14 15:32:50 +08:00
if ((SJ = dyn_cast<StoreInst>(*J)) &&
P.first == SJ->getPointerOperand())
continue;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
if (isSecondInIteratorPair<Value*>(*J, IPairRange))
ConnectedPairs.insert(VPPair(P, ValuePair(*I, *J)));
}
}
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
if (Config.SplatBreaksChain) return;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// Look for cases where just the second value in the pair is used by
// both members of another pair (splatting).
for (Value::use_iterator I = P.second->use_begin(),
E = P.second->use_end(); I != E; ++I) {
Fix an error in BBVectorize important for vectorizing pointer types. When vectorizing pointer types it is important to realize that potential pairs cannot be connected via the address pointer argument of a load or store. This is because even after vectorization, the address is still a scalar because the address of the higher half of the pair is implicit from the address of the lower half (it need not be, and should not be, explicitly computed). llvm-svn: 154735
2012-04-14 15:32:50 +08:00
if (isa<LoadInst>(*I))
continue;
else if ((SI = dyn_cast<StoreInst>(*I)) &&
P.second == SI->getPointerOperand())
continue;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
VPIteratorPair IPairRange = CandidatePairs.equal_range(*I);
for (Value::use_iterator J = P.second->use_begin(); J != E; ++J) {
Fix an error in BBVectorize important for vectorizing pointer types. When vectorizing pointer types it is important to realize that potential pairs cannot be connected via the address pointer argument of a load or store. This is because even after vectorization, the address is still a scalar because the address of the higher half of the pair is implicit from the address of the lower half (it need not be, and should not be, explicitly computed). llvm-svn: 154735
2012-04-14 15:32:50 +08:00
if ((SJ = dyn_cast<StoreInst>(*J)) &&
P.second == SJ->getPointerOperand())
continue;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
if (isSecondInIteratorPair<Value*>(*J, IPairRange))
ConnectedPairs.insert(VPPair(P, ValuePair(*I, *J)));
}
}
}
// This function figures out which pairs are connected. Two pairs are
// connected if some output of the first pair forms an input to both members
// of the second pair.
void BBVectorize::computeConnectedPairs(
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs) {
for (std::vector<Value *>::iterator PI = PairableInsts.begin(),
PE = PairableInsts.end(); PI != PE; ++PI) {
VPIteratorPair choiceRange = CandidatePairs.equal_range(*PI);
for (std::multimap<Value *, Value *>::iterator P = choiceRange.first;
P != choiceRange.second; ++P)
computePairsConnectedTo(CandidatePairs, PairableInsts,
ConnectedPairs, *P);
}
DEBUG(dbgs() << "BBV: found " << ConnectedPairs.size()
<< " pair connections.\n");
}
// This function builds a set of use tuples such that <A, B> is in the set
// if B is in the use tree of A. If B is in the use tree of A, then B
// depends on the output of A.
void BBVectorize::buildDepMap(
BasicBlock &BB,
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
DenseSet<ValuePair> &PairableInstUsers) {
DenseSet<Value *> IsInPair;
for (std::multimap<Value *, Value *>::iterator C = CandidatePairs.begin(),
E = CandidatePairs.end(); C != E; ++C) {
IsInPair.insert(C->first);
IsInPair.insert(C->second);
}
// Iterate through the basic block, recording all Users of each
// pairable instruction.
BasicBlock::iterator E = BB.end();
for (BasicBlock::iterator I = BB.getFirstInsertionPt(); I != E; ++I) {
if (IsInPair.find(I) == IsInPair.end()) continue;
DenseSet<Value *> Users;
AliasSetTracker WriteSet(*AA);
for (BasicBlock::iterator J = llvm::next(I); J != E; ++J)
(void) trackUsesOfI(Users, WriteSet, I, J);
for (DenseSet<Value *>::iterator U = Users.begin(), E = Users.end();
U != E; ++U)
PairableInstUsers.insert(ValuePair(I, *U));
}
}
// Returns true if an input to pair P is an output of pair Q and also an
// input of pair Q is an output of pair P. If this is the case, then these
// two pairs cannot be simultaneously fused.
bool BBVectorize::pairsConflict(ValuePair P, ValuePair Q,
DenseSet<ValuePair> &PairableInstUsers,
std::multimap<ValuePair, ValuePair> *PairableInstUserMap) {
// Two pairs are in conflict if they are mutual Users of eachother.
bool QUsesP = PairableInstUsers.count(ValuePair(P.first, Q.first)) ||
PairableInstUsers.count(ValuePair(P.first, Q.second)) ||
PairableInstUsers.count(ValuePair(P.second, Q.first)) ||
PairableInstUsers.count(ValuePair(P.second, Q.second));
bool PUsesQ = PairableInstUsers.count(ValuePair(Q.first, P.first)) ||
PairableInstUsers.count(ValuePair(Q.first, P.second)) ||
PairableInstUsers.count(ValuePair(Q.second, P.first)) ||
PairableInstUsers.count(ValuePair(Q.second, P.second));
if (PairableInstUserMap) {
// FIXME: The expensive part of the cycle check is not so much the cycle
// check itself but this edge insertion procedure. This needs some
// profiling and probably a different data structure (same is true of
// most uses of std::multimap).
if (PUsesQ) {
VPPIteratorPair QPairRange = PairableInstUserMap->equal_range(Q);
if (!isSecondInIteratorPair(P, QPairRange))
PairableInstUserMap->insert(VPPair(Q, P));
}
if (QUsesP) {
VPPIteratorPair PPairRange = PairableInstUserMap->equal_range(P);
if (!isSecondInIteratorPair(Q, PPairRange))
PairableInstUserMap->insert(VPPair(P, Q));
}
}
return (QUsesP && PUsesQ);
}
// This function walks the use graph of current pairs to see if, starting
// from P, the walk returns to P.
bool BBVectorize::pairWillFormCycle(ValuePair P,
std::multimap<ValuePair, ValuePair> &PairableInstUserMap,
DenseSet<ValuePair> &CurrentPairs) {
DEBUG(if (DebugCycleCheck)
dbgs() << "BBV: starting cycle check for : " << *P.first << " <-> "
<< *P.second << "\n");
// A lookup table of visisted pairs is kept because the PairableInstUserMap
// contains non-direct associations.
DenseSet<ValuePair> Visited;
Minor changes from review. As suggested by Nick Lewycky, the tree traversal queues have been changed to SmallVectors and the associated loops have been rotated. Also, an 80-col violation was fixed. llvm-svn: 149607
2012-02-03 01:29:39 +08:00
SmallVector<ValuePair, 32> Q;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// General depth-first post-order traversal:
Q.push_back(P);
Minor changes from review. As suggested by Nick Lewycky, the tree traversal queues have been changed to SmallVectors and the associated loops have been rotated. Also, an 80-col violation was fixed. llvm-svn: 149607
2012-02-03 01:29:39 +08:00
do {
ValuePair QTop = Q.pop_back_val();
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Visited.insert(QTop);
DEBUG(if (DebugCycleCheck)
dbgs() << "BBV: cycle check visiting: " << *QTop.first << " <-> "
<< *QTop.second << "\n");
VPPIteratorPair QPairRange = PairableInstUserMap.equal_range(QTop);
for (std::multimap<ValuePair, ValuePair>::iterator C = QPairRange.first;
C != QPairRange.second; ++C) {
if (C->second == P) {
DEBUG(dbgs()
<< "BBV: rejected to prevent non-trivial cycle formation: "
<< *C->first.first << " <-> " << *C->first.second << "\n");
return true;
}
Simplify contains tests using 'count'. llvm-svn: 149813
2012-02-05 14:35:36 +08:00
if (CurrentPairs.count(C->second) && !Visited.count(C->second))
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Q.push_back(C->second);
}
Minor changes from review. As suggested by Nick Lewycky, the tree traversal queues have been changed to SmallVectors and the associated loops have been rotated. Also, an 80-col violation was fixed. llvm-svn: 149607
2012-02-03 01:29:39 +08:00
} while (!Q.empty());
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return false;
}
// This function builds the initial tree of connected pairs with the
// pair J at the root.
void BBVectorize::buildInitialTreeFor(
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs,
DenseSet<ValuePair> &PairableInstUsers,
DenseMap<Value *, Value *> &ChosenPairs,
DenseMap<ValuePair, size_t> &Tree, ValuePair J) {
// Each of these pairs is viewed as the root node of a Tree. The Tree
// is then walked (depth-first). As this happens, we keep track of
// the pairs that compose the Tree and the maximum depth of the Tree.
Minor changes from review. As suggested by Nick Lewycky, the tree traversal queues have been changed to SmallVectors and the associated loops have been rotated. Also, an 80-col violation was fixed. llvm-svn: 149607
2012-02-03 01:29:39 +08:00
SmallVector<ValuePairWithDepth, 32> Q;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// General depth-first post-order traversal:
Q.push_back(ValuePairWithDepth(J, getDepthFactor(J.first)));
Minor changes from review. As suggested by Nick Lewycky, the tree traversal queues have been changed to SmallVectors and the associated loops have been rotated. Also, an 80-col violation was fixed. llvm-svn: 149607
2012-02-03 01:29:39 +08:00
do {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
ValuePairWithDepth QTop = Q.back();
// Push each child onto the queue:
bool MoreChildren = false;
size_t MaxChildDepth = QTop.second;
VPPIteratorPair qtRange = ConnectedPairs.equal_range(QTop.first);
BBVectorize.cpp: Try to fix MSVC build. map::iterator and multimap::iterator are incompatible. llvm-svn: 149475
2012-02-01 14:11:58 +08:00
for (std::multimap<ValuePair, ValuePair>::iterator k = qtRange.first;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
k != qtRange.second; ++k) {
// Make sure that this child pair is still a candidate:
bool IsStillCand = false;
VPIteratorPair checkRange =
CandidatePairs.equal_range(k->second.first);
for (std::multimap<Value *, Value *>::iterator m = checkRange.first;
m != checkRange.second; ++m) {
if (m->second == k->second.second) {
IsStillCand = true;
break;
}
}
if (IsStillCand) {
DenseMap<ValuePair, size_t>::iterator C = Tree.find(k->second);
if (C == Tree.end()) {
size_t d = getDepthFactor(k->second.first);
Q.push_back(ValuePairWithDepth(k->second, QTop.second+d));
MoreChildren = true;
} else {
MaxChildDepth = std::max(MaxChildDepth, C->second);
}
}
}
if (!MoreChildren) {
// Record the current pair as part of the Tree:
Tree.insert(ValuePairWithDepth(QTop.first, MaxChildDepth));
Q.pop_back();
}
Minor changes from review. As suggested by Nick Lewycky, the tree traversal queues have been changed to SmallVectors and the associated loops have been rotated. Also, an 80-col violation was fixed. llvm-svn: 149607
2012-02-03 01:29:39 +08:00
} while (!Q.empty());
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
// Given some initial tree, prune it by removing conflicting pairs (pairs
// that cannot be simultaneously chosen for vectorization).
void BBVectorize::pruneTreeFor(
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs,
DenseSet<ValuePair> &PairableInstUsers,
std::multimap<ValuePair, ValuePair> &PairableInstUserMap,
DenseMap<Value *, Value *> &ChosenPairs,
DenseMap<ValuePair, size_t> &Tree,
DenseSet<ValuePair> &PrunedTree, ValuePair J,
bool UseCycleCheck) {
Minor changes from review. As suggested by Nick Lewycky, the tree traversal queues have been changed to SmallVectors and the associated loops have been rotated. Also, an 80-col violation was fixed. llvm-svn: 149607
2012-02-03 01:29:39 +08:00
SmallVector<ValuePairWithDepth, 32> Q;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// General depth-first post-order traversal:
Q.push_back(ValuePairWithDepth(J, getDepthFactor(J.first)));
Minor changes from review. As suggested by Nick Lewycky, the tree traversal queues have been changed to SmallVectors and the associated loops have been rotated. Also, an 80-col violation was fixed. llvm-svn: 149607
2012-02-03 01:29:39 +08:00
do {
ValuePairWithDepth QTop = Q.pop_back_val();
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
PrunedTree.insert(QTop.first);
// Visit each child, pruning as necessary...
fix typos llvm-svn: 152035
2012-03-06 01:39:47 +08:00
DenseMap<ValuePair, size_t> BestChildren;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
VPPIteratorPair QTopRange = ConnectedPairs.equal_range(QTop.first);
BBVectorize.cpp: Try to fix MSVC build. map::iterator and multimap::iterator are incompatible. llvm-svn: 149475
2012-02-01 14:11:58 +08:00
for (std::multimap<ValuePair, ValuePair>::iterator K = QTopRange.first;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
K != QTopRange.second; ++K) {
DenseMap<ValuePair, size_t>::iterator C = Tree.find(K->second);
if (C == Tree.end()) continue;
// This child is in the Tree, now we need to make sure it is the
// best of any conflicting children. There could be multiple
// conflicting children, so first, determine if we're keeping
// this child, then delete conflicting children as necessary.
// It is also necessary to guard against pairing-induced
// dependencies. Consider instructions a .. x .. y .. b
// such that (a,b) are to be fused and (x,y) are to be fused
// but a is an input to x and b is an output from y. This
// means that y cannot be moved after b but x must be moved
// after b for (a,b) to be fused. In other words, after
// fusing (a,b) we have y .. a/b .. x where y is an input
// to a/b and x is an output to a/b: x and y can no longer
// be legally fused. To prevent this condition, we must
// make sure that a child pair added to the Tree is not
// both an input and output of an already-selected pair.
// Pairing-induced dependencies can also form from more complicated
// cycles. The pair vs. pair conflicts are easy to check, and so
// that is done explicitly for "fast rejection", and because for
// child vs. child conflicts, we may prefer to keep the current
// pair in preference to the already-selected child.
DenseSet<ValuePair> CurrentPairs;
bool CanAdd = true;
for (DenseMap<ValuePair, size_t>::iterator C2
fix typos llvm-svn: 152035
2012-03-06 01:39:47 +08:00
= BestChildren.begin(), E2 = BestChildren.end();
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
C2 != E2; ++C2) {
if (C2->first.first == C->first.first ||
C2->first.first == C->first.second ||
C2->first.second == C->first.first ||
C2->first.second == C->first.second ||
pairsConflict(C2->first, C->first, PairableInstUsers,
UseCycleCheck ? &PairableInstUserMap : 0)) {
if (C2->second >= C->second) {
CanAdd = false;
break;
}
CurrentPairs.insert(C2->first);
}
}
if (!CanAdd) continue;
// Even worse, this child could conflict with another node already
// selected for the Tree. If that is the case, ignore this child.
for (DenseSet<ValuePair>::iterator T = PrunedTree.begin(),
E2 = PrunedTree.end(); T != E2; ++T) {
if (T->first == C->first.first ||
T->first == C->first.second ||
T->second == C->first.first ||
T->second == C->first.second ||
pairsConflict(*T, C->first, PairableInstUsers,
UseCycleCheck ? &PairableInstUserMap : 0)) {
CanAdd = false;
break;
}
CurrentPairs.insert(*T);
}
if (!CanAdd) continue;
// And check the queue too...
Minor changes from review. As suggested by Nick Lewycky, the tree traversal queues have been changed to SmallVectors and the associated loops have been rotated. Also, an 80-col violation was fixed. llvm-svn: 149607
2012-02-03 01:29:39 +08:00
for (SmallVector<ValuePairWithDepth, 32>::iterator C2 = Q.begin(),
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
E2 = Q.end(); C2 != E2; ++C2) {
if (C2->first.first == C->first.first ||
C2->first.first == C->first.second ||
C2->first.second == C->first.first ||
C2->first.second == C->first.second ||
pairsConflict(C2->first, C->first, PairableInstUsers,
UseCycleCheck ? &PairableInstUserMap : 0)) {
CanAdd = false;
break;
}
CurrentPairs.insert(C2->first);
}
if (!CanAdd) continue;
// Last but not least, check for a conflict with any of the
// already-chosen pairs.
for (DenseMap<Value *, Value *>::iterator C2 =
ChosenPairs.begin(), E2 = ChosenPairs.end();
C2 != E2; ++C2) {
if (pairsConflict(*C2, C->first, PairableInstUsers,
UseCycleCheck ? &PairableInstUserMap : 0)) {
CanAdd = false;
break;
}
CurrentPairs.insert(*C2);
}
if (!CanAdd) continue;
fix indentation llvm-svn: 149857
2012-02-06 13:29:32 +08:00
// To check for non-trivial cycles formed by the addition of the
// current pair we've formed a list of all relevant pairs, now use a
// graph walk to check for a cycle. We start from the current pair and
// walk the use tree to see if we again reach the current pair. If we
// do, then the current pair is rejected.
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// FIXME: It may be more efficient to use a topological-ordering
// algorithm to improve the cycle check. This should be investigated.
if (UseCycleCheck &&
pairWillFormCycle(C->first, PairableInstUserMap, CurrentPairs))
continue;
// This child can be added, but we may have chosen it in preference
// to an already-selected child. Check for this here, and if a
// conflict is found, then remove the previously-selected child
// before adding this one in its place.
for (DenseMap<ValuePair, size_t>::iterator C2
fix typos llvm-svn: 152035
2012-03-06 01:39:47 +08:00
= BestChildren.begin(); C2 != BestChildren.end();) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
if (C2->first.first == C->first.first ||
C2->first.first == C->first.second ||
C2->first.second == C->first.first ||
C2->first.second == C->first.second ||
pairsConflict(C2->first, C->first, PairableInstUsers))
fix typos llvm-svn: 152035
2012-03-06 01:39:47 +08:00
BestChildren.erase(C2++);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
else
++C2;
}
fix typos llvm-svn: 152035
2012-03-06 01:39:47 +08:00
BestChildren.insert(ValuePairWithDepth(C->first, C->second));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
for (DenseMap<ValuePair, size_t>::iterator C
fix typos llvm-svn: 152035
2012-03-06 01:39:47 +08:00
= BestChildren.begin(), E2 = BestChildren.end();
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
C != E2; ++C) {
size_t DepthF = getDepthFactor(C->first.first);
Q.push_back(ValuePairWithDepth(C->first, QTop.second+DepthF));
}
Minor changes from review. As suggested by Nick Lewycky, the tree traversal queues have been changed to SmallVectors and the associated loops have been rotated. Also, an 80-col violation was fixed. llvm-svn: 149607
2012-02-03 01:29:39 +08:00
} while (!Q.empty());
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
// This function finds the best tree of mututally-compatible connected
// pairs, given the choice of root pairs as an iterator range.
void BBVectorize::findBestTreeFor(
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs,
DenseSet<ValuePair> &PairableInstUsers,
std::multimap<ValuePair, ValuePair> &PairableInstUserMap,
DenseMap<Value *, Value *> &ChosenPairs,
DenseSet<ValuePair> &BestTree, size_t &BestMaxDepth,
size_t &BestEffSize, VPIteratorPair ChoiceRange,
bool UseCycleCheck) {
for (std::multimap<Value *, Value *>::iterator J = ChoiceRange.first;
J != ChoiceRange.second; ++J) {
// Before going any further, make sure that this pair does not
// conflict with any already-selected pairs (see comment below
// near the Tree pruning for more details).
DenseSet<ValuePair> ChosenPairSet;
bool DoesConflict = false;
for (DenseMap<Value *, Value *>::iterator C = ChosenPairs.begin(),
E = ChosenPairs.end(); C != E; ++C) {
if (pairsConflict(*C, *J, PairableInstUsers,
UseCycleCheck ? &PairableInstUserMap : 0)) {
DoesConflict = true;
break;
}
ChosenPairSet.insert(*C);
}
if (DoesConflict) continue;
if (UseCycleCheck &&
pairWillFormCycle(*J, PairableInstUserMap, ChosenPairSet))
continue;
DenseMap<ValuePair, size_t> Tree;
buildInitialTreeFor(CandidatePairs, PairableInsts, ConnectedPairs,
PairableInstUsers, ChosenPairs, Tree, *J);
// Because we'll keep the child with the largest depth, the largest
// depth is still the same in the unpruned Tree.
size_t MaxDepth = Tree.lookup(*J);
DEBUG(if (DebugPairSelection) dbgs() << "BBV: found Tree for pair {"
<< *J->first << " <-> " << *J->second << "} of depth " <<
MaxDepth << " and size " << Tree.size() << "\n");
// At this point the Tree has been constructed, but, may contain
// contradictory children (meaning that different children of
// some tree node may be attempting to fuse the same instruction).
// So now we walk the tree again, in the case of a conflict,
// keep only the child with the largest depth. To break a tie,
// favor the first child.
DenseSet<ValuePair> PrunedTree;
pruneTreeFor(CandidatePairs, PairableInsts, ConnectedPairs,
PairableInstUsers, PairableInstUserMap, ChosenPairs, Tree,
PrunedTree, *J, UseCycleCheck);
size_t EffSize = 0;
for (DenseSet<ValuePair>::iterator S = PrunedTree.begin(),
E = PrunedTree.end(); S != E; ++S)
EffSize += getDepthFactor(S->first);
DEBUG(if (DebugPairSelection)
dbgs() << "BBV: found pruned Tree for pair {"
<< *J->first << " <-> " << *J->second << "} of depth " <<
MaxDepth << " and size " << PrunedTree.size() <<
" (effective size: " << EffSize << ")\n");
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
if (MaxDepth >= Config.ReqChainDepth && EffSize > BestEffSize) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
BestMaxDepth = MaxDepth;
BestEffSize = EffSize;
BestTree = PrunedTree;
}
}
}
// Given the list of candidate pairs, this function selects those
// that will be fused into vector instructions.
void BBVectorize::choosePairs(
std::multimap<Value *, Value *> &CandidatePairs,
std::vector<Value *> &PairableInsts,
std::multimap<ValuePair, ValuePair> &ConnectedPairs,
DenseSet<ValuePair> &PairableInstUsers,
DenseMap<Value *, Value *>& ChosenPairs) {
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
bool UseCycleCheck =
CandidatePairs.size() <= Config.MaxCandPairsForCycleCheck;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
std::multimap<ValuePair, ValuePair> PairableInstUserMap;
for (std::vector<Value *>::iterator I = PairableInsts.begin(),
E = PairableInsts.end(); I != E; ++I) {
// The number of possible pairings for this variable:
size_t NumChoices = CandidatePairs.count(*I);
if (!NumChoices) continue;
VPIteratorPair ChoiceRange = CandidatePairs.equal_range(*I);
// The best pair to choose and its tree:
size_t BestMaxDepth = 0, BestEffSize = 0;
DenseSet<ValuePair> BestTree;
findBestTreeFor(CandidatePairs, PairableInsts, ConnectedPairs,
PairableInstUsers, PairableInstUserMap, ChosenPairs,
BestTree, BestMaxDepth, BestEffSize, ChoiceRange,
UseCycleCheck);
// A tree has been chosen (or not) at this point. If no tree was
// chosen, then this instruction, I, cannot be paired (and is no longer
// considered).
DEBUG(if (BestTree.size() > 0)
dbgs() << "BBV: selected pairs in the best tree for: "
<< *cast<Instruction>(*I) << "\n");
for (DenseSet<ValuePair>::iterator S = BestTree.begin(),
SE2 = BestTree.end(); S != SE2; ++S) {
// Insert the members of this tree into the list of chosen pairs.
ChosenPairs.insert(ValuePair(S->first, S->second));
DEBUG(dbgs() << "BBV: selected pair: " << *S->first << " <-> " <<
*S->second << "\n");
// Remove all candidate pairs that have values in the chosen tree.
for (std::multimap<Value *, Value *>::iterator K =
CandidatePairs.begin(); K != CandidatePairs.end();) {
if (K->first == S->first || K->second == S->first ||
K->second == S->second || K->first == S->second) {
// Don't remove the actual pair chosen so that it can be used
// in subsequent tree selections.
if (!(K->first == S->first && K->second == S->second))
CandidatePairs.erase(K++);
else
++K;
} else {
++K;
}
}
}
}
DEBUG(dbgs() << "BBV: selected " << ChosenPairs.size() << " pairs.\n");
}
std::string getReplacementName(Instruction *I, bool IsInput, unsigned o,
unsigned n = 0) {
if (!I->hasName())
return "";
return (I->getName() + (IsInput ? ".v.i" : ".v.r") + utostr(o) +
(n > 0 ? "." + utostr(n) : "")).str();
}
// Returns the value that is to be used as the pointer input to the vector
// instruction that fuses I with J.
Value *BBVectorize::getReplacementPointerInput(LLVMContext& Context,
Instruction *I, Instruction *J, unsigned o,
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
bool FlipMemInputs) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Value *IPtr, *JPtr;
unsigned IAlignment, JAlignment;
int64_t OffsetInElmts;
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
// Note: the analysis might fail here, that is why FlipMemInputs has
// been precomputed (OffsetInElmts must be unused here).
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
(void) getPairPtrInfo(I, J, IPtr, JPtr, IAlignment, JAlignment,
OffsetInElmts);
// The pointer value is taken to be the one with the lowest offset.
Value *VPtr;
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
if (!FlipMemInputs) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
VPtr = IPtr;
} else {
VPtr = JPtr;
}
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Type *ArgTypeI = cast<PointerType>(IPtr->getType())->getElementType();
Type *ArgTypeJ = cast<PointerType>(JPtr->getType())->getElementType();
Type *VArgType = getVecTypeForPair(ArgTypeI, ArgTypeJ);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Type *VArgPtrType = PointerType::get(VArgType,
cast<PointerType>(IPtr->getType())->getAddressSpace());
return new BitCastInst(VPtr, VArgPtrType, getReplacementName(I, true, o),
/* insert before */ FlipMemInputs ? J : I);
}
void BBVectorize::fillNewShuffleMask(LLVMContext& Context, Instruction *J,
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
unsigned MaskOffset, unsigned NumInElem,
unsigned NumInElem1, unsigned IdxOffset,
std::vector<Constant*> &Mask) {
unsigned NumElem1 = cast<VectorType>(J->getType())->getNumElements();
for (unsigned v = 0; v < NumElem1; ++v) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
int m = cast<ShuffleVectorInst>(J)->getMaskValue(v);
if (m < 0) {
Mask[v+MaskOffset] = UndefValue::get(Type::getInt32Ty(Context));
} else {
unsigned mm = m + (int) IdxOffset;
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
if (m >= (int) NumInElem1)
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
mm += (int) NumInElem;
Mask[v+MaskOffset] =
ConstantInt::get(Type::getInt32Ty(Context), mm);
}
}
}
// Returns the value that is to be used as the vector-shuffle mask to the
// vector instruction that fuses I with J.
Value *BBVectorize::getReplacementShuffleMask(LLVMContext& Context,
Instruction *I, Instruction *J) {
// This is the shuffle mask. We need to append the second
// mask to the first, and the numbers need to be adjusted.
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Type *ArgTypeI = I->getType();
Type *ArgTypeJ = J->getType();
Type *VArgType = getVecTypeForPair(ArgTypeI, ArgTypeJ);
unsigned NumElemI = cast<VectorType>(ArgTypeI)->getNumElements();
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// Get the total number of elements in the fused vector type.
// By definition, this must equal the number of elements in
// the final mask.
unsigned NumElem = cast<VectorType>(VArgType)->getNumElements();
std::vector<Constant*> Mask(NumElem);
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Type *OpTypeI = I->getOperand(0)->getType();
unsigned NumInElemI = cast<VectorType>(OpTypeI)->getNumElements();
Type *OpTypeJ = J->getOperand(0)->getType();
unsigned NumInElemJ = cast<VectorType>(OpTypeJ)->getNumElements();
// The fused vector will be:
// -----------------------------------------------------
// | NumInElemI | NumInElemJ | NumInElemI | NumInElemJ |
// -----------------------------------------------------
// from which we'll extract NumElem total elements (where the first NumElemI
// of them come from the mask in I and the remainder come from the mask
// in J.
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// For the mask from the first pair...
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
fillNewShuffleMask(Context, I, 0, NumInElemJ, NumInElemI,
0, Mask);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// For the mask from the second pair...
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
fillNewShuffleMask(Context, J, NumElemI, NumInElemI, NumInElemJ,
NumInElemI, Mask);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
return ConstantVector::get(Mask);
}
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
bool BBVectorize::expandIEChain(LLVMContext& Context, Instruction *I,
Instruction *J, unsigned o, Value *&LOp,
unsigned numElemL,
Type *ArgTypeL, Type *ArgTypeH,
unsigned IdxOff) {
bool ExpandedIEChain = false;
if (InsertElementInst *LIE = dyn_cast<InsertElementInst>(LOp)) {
// If we have a pure insertelement chain, then this can be rewritten
// into a chain that directly builds the larger type.
bool PureChain = true;
InsertElementInst *LIENext = LIE;
do {
if (!isa<UndefValue>(LIENext->getOperand(0)) &&
!isa<InsertElementInst>(LIENext->getOperand(0))) {
PureChain = false;
break;
}
} while ((LIENext =
dyn_cast<InsertElementInst>(LIENext->getOperand(0))));
if (PureChain) {
SmallVector<Value *, 8> VectElemts(numElemL,
UndefValue::get(ArgTypeL->getScalarType()));
InsertElementInst *LIENext = LIE;
do {
unsigned Idx =
cast<ConstantInt>(LIENext->getOperand(2))->getSExtValue();
VectElemts[Idx] = LIENext->getOperand(1);
} while ((LIENext =
dyn_cast<InsertElementInst>(LIENext->getOperand(0))));
LIENext = 0;
Value *LIEPrev = UndefValue::get(ArgTypeH);
for (unsigned i = 0; i < numElemL; ++i) {
if (isa<UndefValue>(VectElemts[i])) continue;
LIENext = InsertElementInst::Create(LIEPrev, VectElemts[i],
ConstantInt::get(Type::getInt32Ty(Context),
i + IdxOff),
getReplacementName(I, true, o, i+1));
LIENext->insertBefore(J);
LIEPrev = LIENext;
}
LOp = LIENext ? (Value*) LIENext : UndefValue::get(ArgTypeH);
ExpandedIEChain = true;
}
}
return ExpandedIEChain;
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// Returns the value to be used as the specified operand of the vector
// instruction that fuses I with J.
Value *BBVectorize::getReplacementInput(LLVMContext& Context, Instruction *I,
Instruction *J, unsigned o, bool FlipMemInputs) {
Value *CV0 = ConstantInt::get(Type::getInt32Ty(Context), 0);
Value *CV1 = ConstantInt::get(Type::getInt32Ty(Context), 1);
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
// Compute the fused vector type for this operand
Type *ArgTypeI = I->getOperand(o)->getType();
Type *ArgTypeJ = J->getOperand(o)->getType();
VectorType *VArgType = getVecTypeForPair(ArgTypeI, ArgTypeJ);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Instruction *L = I, *H = J;
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Type *ArgTypeL = ArgTypeI, *ArgTypeH = ArgTypeJ;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
if (FlipMemInputs) {
L = J;
H = I;
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
ArgTypeL = ArgTypeJ;
ArgTypeH = ArgTypeI;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
unsigned numElemL;
if (ArgTypeL->isVectorTy())
numElemL = cast<VectorType>(ArgTypeL)->getNumElements();
else
numElemL = 1;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
unsigned numElemH;
if (ArgTypeH->isVectorTy())
numElemH = cast<VectorType>(ArgTypeH)->getNumElements();
else
numElemH = 1;
Value *LOp = L->getOperand(o);
Value *HOp = H->getOperand(o);
unsigned numElem = VArgType->getNumElements();
// First, we check if we can reuse the "original" vector outputs (if these
// exist). We might need a shuffle.
ExtractElementInst *LEE = dyn_cast<ExtractElementInst>(LOp);
ExtractElementInst *HEE = dyn_cast<ExtractElementInst>(HOp);
ShuffleVectorInst *LSV = dyn_cast<ShuffleVectorInst>(LOp);
ShuffleVectorInst *HSV = dyn_cast<ShuffleVectorInst>(HOp);
// FIXME: If we're fusing shuffle instructions, then we can't apply this
// optimization. The input vectors to the shuffle might be a different
// length from the shuffle outputs. Unfortunately, the replacement
// shuffle mask has already been formed, and the mask entries are sensitive
// to the sizes of the inputs.
bool IsSizeChangeShuffle =
isa<ShuffleVectorInst>(L) &&
(LOp->getType() != L->getType() || HOp->getType() != H->getType());
if ((LEE || LSV) && (HEE || HSV) && !IsSizeChangeShuffle) {
// We can have at most two unique vector inputs.
bool CanUseInputs = true;
Value *I1, *I2 = 0;
if (LEE) {
I1 = LEE->getOperand(0);
} else {
I1 = LSV->getOperand(0);
I2 = LSV->getOperand(1);
if (I2 == I1 || isa<UndefValue>(I2))
I2 = 0;
}
if (HEE) {
Value *I3 = HEE->getOperand(0);
if (!I2 && I3 != I1)
I2 = I3;
else if (I3 != I1 && I3 != I2)
CanUseInputs = false;
} else {
Value *I3 = HSV->getOperand(0);
if (!I2 && I3 != I1)
I2 = I3;
else if (I3 != I1 && I3 != I2)
CanUseInputs = false;
if (CanUseInputs) {
Value *I4 = HSV->getOperand(1);
if (!isa<UndefValue>(I4)) {
if (!I2 && I4 != I1)
I2 = I4;
else if (I4 != I1 && I4 != I2)
CanUseInputs = false;
}
}
}
if (CanUseInputs) {
unsigned LOpElem =
cast<VectorType>(cast<Instruction>(LOp)->getOperand(0)->getType())
->getNumElements();
unsigned HOpElem =
cast<VectorType>(cast<Instruction>(HOp)->getOperand(0)->getType())
->getNumElements();
// We have one or two input vectors. We need to map each index of the
// operands to the index of the original vector.
SmallVector<std::pair<int, int>, 8> II(numElem);
for (unsigned i = 0; i < numElemL; ++i) {
int Idx, INum;
if (LEE) {
Idx =
cast<ConstantInt>(LEE->getOperand(1))->getSExtValue();
INum = LEE->getOperand(0) == I1 ? 0 : 1;
} else {
Idx = LSV->getMaskValue(i);
if (Idx < (int) LOpElem) {
INum = LSV->getOperand(0) == I1 ? 0 : 1;
} else {
Idx -= LOpElem;
INum = LSV->getOperand(1) == I1 ? 0 : 1;
}
}
II[i] = std::pair<int, int>(Idx, INum);
}
for (unsigned i = 0; i < numElemH; ++i) {
int Idx, INum;
if (HEE) {
Idx =
cast<ConstantInt>(HEE->getOperand(1))->getSExtValue();
INum = HEE->getOperand(0) == I1 ? 0 : 1;
} else {
Idx = HSV->getMaskValue(i);
if (Idx < (int) HOpElem) {
INum = HSV->getOperand(0) == I1 ? 0 : 1;
} else {
Idx -= HOpElem;
INum = HSV->getOperand(1) == I1 ? 0 : 1;
}
}
II[i + numElemL] = std::pair<int, int>(Idx, INum);
}
// We now have an array which tells us from which index of which
// input vector each element of the operand comes.
VectorType *I1T = cast<VectorType>(I1->getType());
unsigned I1Elem = I1T->getNumElements();
if (!I2) {
// In this case there is only one underlying vector input. Check for
// the trivial case where we can use the input directly.
if (I1Elem == numElem) {
bool ElemInOrder = true;
for (unsigned i = 0; i < numElem; ++i) {
if (II[i].first != (int) i && II[i].first != -1) {
ElemInOrder = false;
break;
}
}
if (ElemInOrder)
return I1;
}
// A shuffle is needed.
std::vector<Constant *> Mask(numElem);
for (unsigned i = 0; i < numElem; ++i) {
int Idx = II[i].first;
if (Idx == -1)
Mask[i] = UndefValue::get(Type::getInt32Ty(Context));
else
Mask[i] = ConstantInt::get(Type::getInt32Ty(Context), Idx);
}
Instruction *S =
new ShuffleVectorInst(I1, UndefValue::get(I1T),
ConstantVector::get(Mask),
getReplacementName(I, true, o));
S->insertBefore(J);
return S;
}
VectorType *I2T = cast<VectorType>(I2->getType());
unsigned I2Elem = I2T->getNumElements();
// This input comes from two distinct vectors. The first step is to
// make sure that both vectors are the same length. If not, the
// smaller one will need to grow before they can be shuffled together.
if (I1Elem < I2Elem) {
std::vector<Constant *> Mask(I2Elem);
unsigned v = 0;
for (; v < I1Elem; ++v)
Mask[v] = ConstantInt::get(Type::getInt32Ty(Context), v);
for (; v < I2Elem; ++v)
Mask[v] = UndefValue::get(Type::getInt32Ty(Context));
Instruction *NewI1 =
new ShuffleVectorInst(I1, UndefValue::get(I1T),
ConstantVector::get(Mask),
getReplacementName(I, true, o, 1));
NewI1->insertBefore(J);
I1 = NewI1;
I1T = I2T;
I1Elem = I2Elem;
} else if (I1Elem > I2Elem) {
std::vector<Constant *> Mask(I1Elem);
unsigned v = 0;
for (; v < I2Elem; ++v)
Mask[v] = ConstantInt::get(Type::getInt32Ty(Context), v);
for (; v < I1Elem; ++v)
Mask[v] = UndefValue::get(Type::getInt32Ty(Context));
Instruction *NewI2 =
new ShuffleVectorInst(I2, UndefValue::get(I2T),
ConstantVector::get(Mask),
getReplacementName(I, true, o, 1));
NewI2->insertBefore(J);
I2 = NewI2;
I2T = I1T;
I2Elem = I1Elem;
}
// Now that both I1 and I2 are the same length we can shuffle them
// together (and use the result).
std::vector<Constant *> Mask(numElem);
for (unsigned v = 0; v < numElem; ++v) {
if (II[v].first == -1) {
Mask[v] = UndefValue::get(Type::getInt32Ty(Context));
} else {
int Idx = II[v].first + II[v].second * I1Elem;
Mask[v] = ConstantInt::get(Type::getInt32Ty(Context), Idx);
}
}
Instruction *NewOp =
new ShuffleVectorInst(I1, I2, ConstantVector::get(Mask),
getReplacementName(I, true, o));
NewOp->insertBefore(J);
return NewOp;
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Type *ArgType = ArgTypeL;
if (numElemL < numElemH) {
if (numElemL == 1 && expandIEChain(Context, I, J, o, HOp, numElemH,
ArgTypeL, VArgType, 1)) {
// This is another short-circuit case: we're combining a scalar into
// a vector that is formed by an IE chain. We've just expanded the IE
// chain, now insert the scalar and we're done.
Instruction *S = InsertElementInst::Create(HOp, LOp, CV0,
getReplacementName(I, true, o));
S->insertBefore(J);
return S;
} else if (!expandIEChain(Context, I, J, o, LOp, numElemL, ArgTypeL,
ArgTypeH)) {
// The two vector inputs to the shuffle must be the same length,
// so extend the smaller vector to be the same length as the larger one.
Instruction *NLOp;
if (numElemL > 1) {
std::vector<Constant *> Mask(numElemH);
unsigned v = 0;
for (; v < numElemL; ++v)
Mask[v] = ConstantInt::get(Type::getInt32Ty(Context), v);
for (; v < numElemH; ++v)
Mask[v] = UndefValue::get(Type::getInt32Ty(Context));
NLOp = new ShuffleVectorInst(LOp, UndefValue::get(ArgTypeL),
ConstantVector::get(Mask),
getReplacementName(I, true, o, 1));
} else {
NLOp = InsertElementInst::Create(UndefValue::get(ArgTypeH), LOp, CV0,
getReplacementName(I, true, o, 1));
}
NLOp->insertBefore(J);
LOp = NLOp;
}
ArgType = ArgTypeH;
} else if (numElemL > numElemH) {
if (numElemH == 1 && expandIEChain(Context, I, J, o, LOp, numElemL,
ArgTypeH, VArgType)) {
Instruction *S =
InsertElementInst::Create(LOp, HOp,
ConstantInt::get(Type::getInt32Ty(Context),
numElemL),
getReplacementName(I, true, o));
S->insertBefore(J);
return S;
} else if (!expandIEChain(Context, I, J, o, HOp, numElemH, ArgTypeH,
ArgTypeL)) {
Instruction *NHOp;
if (numElemH > 1) {
std::vector<Constant *> Mask(numElemL);
unsigned v = 0;
for (; v < numElemH; ++v)
Mask[v] = ConstantInt::get(Type::getInt32Ty(Context), v);
for (; v < numElemL; ++v)
Mask[v] = UndefValue::get(Type::getInt32Ty(Context));
NHOp = new ShuffleVectorInst(HOp, UndefValue::get(ArgTypeH),
ConstantVector::get(Mask),
getReplacementName(I, true, o, 1));
} else {
NHOp = InsertElementInst::Create(UndefValue::get(ArgTypeL), HOp, CV0,
getReplacementName(I, true, o, 1));
}
NHOp->insertBefore(J);
HOp = NHOp;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
if (ArgType->isVectorTy()) {
unsigned numElem = cast<VectorType>(VArgType)->getNumElements();
std::vector<Constant*> Mask(numElem);
for (unsigned v = 0; v < numElem; ++v) {
unsigned Idx = v;
// If the low vector was expanded, we need to skip the extra
// undefined entries.
if (v >= numElemL && numElemH > numElemL)
Idx += (numElemH - numElemL);
Mask[v] = ConstantInt::get(Type::getInt32Ty(Context), Idx);
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Instruction *BV = new ShuffleVectorInst(LOp, HOp,
ConstantVector::get(Mask),
getReplacementName(I, true, o));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
BV->insertBefore(J);
return BV;
}
Instruction *BV1 = InsertElementInst::Create(
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
UndefValue::get(VArgType), LOp, CV0,
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
getReplacementName(I, true, o, 1));
BV1->insertBefore(I);
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Instruction *BV2 = InsertElementInst::Create(BV1, HOp, CV1,
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
getReplacementName(I, true, o, 2));
BV2->insertBefore(J);
return BV2;
}
// This function creates an array of values that will be used as the inputs
// to the vector instruction that fuses I with J.
void BBVectorize::getReplacementInputsForPair(LLVMContext& Context,
Instruction *I, Instruction *J,
SmallVector<Value *, 3> &ReplacedOperands,
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
bool FlipMemInputs) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
unsigned NumOperands = I->getNumOperands();
for (unsigned p = 0, o = NumOperands-1; p < NumOperands; ++p, --o) {
// Iterate backward so that we look at the store pointer
// first and know whether or not we need to flip the inputs.
if (isa<LoadInst>(I) || (o == 1 && isa<StoreInst>(I))) {
// This is the pointer for a load/store instruction.
ReplacedOperands[o] = getReplacementPointerInput(Context, I, J, o,
FlipMemInputs);
continue;
Correctly vectorize powi. The powi intrinsic requires special handling because it always takes a single integer power regardless of the result type. As a result, we can vectorize only if the powers are equal. Fixes PR12364. llvm-svn: 153797
2012-03-31 11:38:40 +08:00
} else if (isa<CallInst>(I)) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Function *F = cast<CallInst>(I)->getCalledFunction();
unsigned IID = F->getIntrinsicID();
Correctly vectorize powi. The powi intrinsic requires special handling because it always takes a single integer power regardless of the result type. As a result, we can vectorize only if the powers are equal. Fixes PR12364. llvm-svn: 153797
2012-03-31 11:38:40 +08:00
if (o == NumOperands-1) {
BasicBlock &BB = *I->getParent();
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
Correctly vectorize powi. The powi intrinsic requires special handling because it always takes a single integer power regardless of the result type. As a result, we can vectorize only if the powers are equal. Fixes PR12364. llvm-svn: 153797
2012-03-31 11:38:40 +08:00
Module *M = BB.getParent()->getParent();
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Type *ArgTypeI = I->getType();
Type *ArgTypeJ = J->getType();
Type *VArgType = getVecTypeForPair(ArgTypeI, ArgTypeJ);
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
Correctly vectorize powi. The powi intrinsic requires special handling because it always takes a single integer power regardless of the result type. As a result, we can vectorize only if the powers are equal. Fixes PR12364. llvm-svn: 153797
2012-03-31 11:38:40 +08:00
ReplacedOperands[o] = Intrinsic::getDeclaration(M,
(Intrinsic::ID) IID, VArgType);
continue;
} else if (IID == Intrinsic::powi && o == 1) {
// The second argument of powi is a single integer and we've already
// checked that both arguments are equal. As a result, we just keep
// I's second argument.
ReplacedOperands[o] = I->getOperand(o);
continue;
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
} else if (isa<ShuffleVectorInst>(I) && o == NumOperands-1) {
ReplacedOperands[o] = getReplacementShuffleMask(Context, I, J);
continue;
}
ReplacedOperands[o] =
getReplacementInput(Context, I, J, o, FlipMemInputs);
}
}
// This function creates two values that represent the outputs of the
// original I and J instructions. These are generally vector shuffles
// or extracts. In many cases, these will end up being unused and, thus,
// eliminated by later passes.
void BBVectorize::replaceOutputsOfPair(LLVMContext& Context, Instruction *I,
Instruction *J, Instruction *K,
Instruction *&InsertionPt,
Instruction *&K1, Instruction *&K2,
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
bool FlipMemInputs) {
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
if (isa<StoreInst>(I)) {
AA->replaceWithNewValue(I, K);
AA->replaceWithNewValue(J, K);
} else {
Type *IType = I->getType();
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Type *JType = J->getType();
VectorType *VType = getVecTypeForPair(IType, JType);
unsigned numElem = VType->getNumElements();
unsigned numElemI, numElemJ;
if (IType->isVectorTy())
numElemI = cast<VectorType>(IType)->getNumElements();
else
numElemI = 1;
if (JType->isVectorTy())
numElemJ = cast<VectorType>(JType)->getNumElements();
else
numElemJ = 1;
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
if (IType->isVectorTy()) {
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
std::vector<Constant*> Mask1(numElemI), Mask2(numElemI);
for (unsigned v = 0; v < numElemI; ++v) {
Mask1[v] = ConstantInt::get(Type::getInt32Ty(Context), v);
Mask2[v] = ConstantInt::get(Type::getInt32Ty(Context), numElemJ+v);
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
K1 = new ShuffleVectorInst(K, UndefValue::get(VType),
ConstantVector::get(
FlipMemInputs ? Mask2 : Mask1),
getReplacementName(K, false, 1));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
} else {
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Value *CV0 = ConstantInt::get(Type::getInt32Ty(Context), 0);
Value *CV1 = ConstantInt::get(Type::getInt32Ty(Context), numElem-1);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
K1 = ExtractElementInst::Create(K, FlipMemInputs ? CV1 : CV0,
getReplacementName(K, false, 1));
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
}
if (JType->isVectorTy()) {
std::vector<Constant*> Mask1(numElemJ), Mask2(numElemJ);
for (unsigned v = 0; v < numElemJ; ++v) {
Mask1[v] = ConstantInt::get(Type::getInt32Ty(Context), v);
Mask2[v] = ConstantInt::get(Type::getInt32Ty(Context), numElemI+v);
}
K2 = new ShuffleVectorInst(K, UndefValue::get(VType),
ConstantVector::get(
FlipMemInputs ? Mask1 : Mask2),
getReplacementName(K, false, 2));
} else {
Value *CV0 = ConstantInt::get(Type::getInt32Ty(Context), 0);
Value *CV1 = ConstantInt::get(Type::getInt32Ty(Context), numElem-1);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
K2 = ExtractElementInst::Create(K, FlipMemInputs ? CV0 : CV1,
getReplacementName(K, false, 2));
}
K1->insertAfter(K);
K2->insertAfter(K1);
InsertionPt = K2;
}
}
// Move all uses of the function I (including pairing-induced uses) after J.
bool BBVectorize::canMoveUsesOfIAfterJ(BasicBlock &BB,
std::multimap<Value *, Value *> &LoadMoveSet,
Instruction *I, Instruction *J) {
// Skip to the first instruction past I.
BBVectorize: Simplify code, no functionality change. Also silences warnings about bodyless for loops. llvm-svn: 149612
2012-02-03 02:52:15 +08:00
BasicBlock::iterator L = llvm::next(BasicBlock::iterator(I));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
DenseSet<Value *> Users;
AliasSetTracker WriteSet(*AA);
for (; cast<Instruction>(L) != J; ++L)
(void) trackUsesOfI(Users, WriteSet, I, L, true, &LoadMoveSet);
assert(cast<Instruction>(L) == J &&
"Tracking has not proceeded far enough to check for dependencies");
// If J is now in the use set of I, then trackUsesOfI will return true
// and we have a dependency cycle (and the fusing operation must abort).
return !trackUsesOfI(Users, WriteSet, I, J, true, &LoadMoveSet);
}
// Move all uses of the function I (including pairing-induced uses) after J.
void BBVectorize::moveUsesOfIAfterJ(BasicBlock &BB,
std::multimap<Value *, Value *> &LoadMoveSet,
Instruction *&InsertionPt,
Instruction *I, Instruction *J) {
// Skip to the first instruction past I.
BBVectorize: Simplify code, no functionality change. Also silences warnings about bodyless for loops. llvm-svn: 149612
2012-02-03 02:52:15 +08:00
BasicBlock::iterator L = llvm::next(BasicBlock::iterator(I));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
DenseSet<Value *> Users;
AliasSetTracker WriteSet(*AA);
for (; cast<Instruction>(L) != J;) {
if (trackUsesOfI(Users, WriteSet, I, L, true, &LoadMoveSet)) {
// Move this instruction
Instruction *InstToMove = L; ++L;
DEBUG(dbgs() << "BBV: moving: " << *InstToMove <<
" to after " << *InsertionPt << "\n");
InstToMove->removeFromParent();
InstToMove->insertAfter(InsertionPt);
InsertionPt = InstToMove;
} else {
++L;
}
}
}
// Collect all load instruction that are in the move set of a given first
// pair member. These loads depend on the first instruction, I, and so need
// to be moved after J (the second instruction) when the pair is fused.
void BBVectorize::collectPairLoadMoveSet(BasicBlock &BB,
DenseMap<Value *, Value *> &ChosenPairs,
std::multimap<Value *, Value *> &LoadMoveSet,
Instruction *I) {
// Skip to the first instruction past I.
BBVectorize: Simplify code, no functionality change. Also silences warnings about bodyless for loops. llvm-svn: 149612
2012-02-03 02:52:15 +08:00
BasicBlock::iterator L = llvm::next(BasicBlock::iterator(I));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
DenseSet<Value *> Users;
AliasSetTracker WriteSet(*AA);
// Note: We cannot end the loop when we reach J because J could be moved
// farther down the use chain by another instruction pairing. Also, J
// could be before I if this is an inverted input.
for (BasicBlock::iterator E = BB.end(); cast<Instruction>(L) != E; ++L) {
if (trackUsesOfI(Users, WriteSet, I, L)) {
if (L->mayReadFromMemory())
LoadMoveSet.insert(ValuePair(L, I));
}
}
}
// In cases where both load/stores and the computation of their pointers
// are chosen for vectorization, we can end up in a situation where the
// aliasing analysis starts returning different query results as the
// process of fusing instruction pairs continues. Because the algorithm
// relies on finding the same use trees here as were found earlier, we'll
// need to precompute the necessary aliasing information here and then
// manually update it during the fusion process.
void BBVectorize::collectLoadMoveSet(BasicBlock &BB,
std::vector<Value *> &PairableInsts,
DenseMap<Value *, Value *> &ChosenPairs,
std::multimap<Value *, Value *> &LoadMoveSet) {
for (std::vector<Value *>::iterator PI = PairableInsts.begin(),
PIE = PairableInsts.end(); PI != PIE; ++PI) {
DenseMap<Value *, Value *>::iterator P = ChosenPairs.find(*PI);
if (P == ChosenPairs.end()) continue;
Instruction *I = cast<Instruction>(P->first);
collectPairLoadMoveSet(BB, ChosenPairs, LoadMoveSet, I);
}
}
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
// As with the aliasing information, SCEV can also change because of
// vectorization. This information is used to compute relative pointer
// offsets; the necessary information will be cached here prior to
// fusion.
void BBVectorize::collectPtrInfo(std::vector<Value *> &PairableInsts,
DenseMap<Value *, Value *> &ChosenPairs,
DenseSet<Value *> &LowPtrInsts) {
for (std::vector<Value *>::iterator PI = PairableInsts.begin(),
PIE = PairableInsts.end(); PI != PIE; ++PI) {
DenseMap<Value *, Value *>::iterator P = ChosenPairs.find(*PI);
if (P == ChosenPairs.end()) continue;
Instruction *I = cast<Instruction>(P->first);
Instruction *J = cast<Instruction>(P->second);
if (!isa<LoadInst>(I) && !isa<StoreInst>(I))
continue;
Value *IPtr, *JPtr;
unsigned IAlignment, JAlignment;
int64_t OffsetInElmts;
if (!getPairPtrInfo(I, J, IPtr, JPtr, IAlignment, JAlignment,
OffsetInElmts) || abs64(OffsetInElmts) != 1)
llvm_unreachable("Pre-fusion pointer analysis failed");
Value *LowPI = (OffsetInElmts > 0) ? I : J;
LowPtrInsts.insert(LowPI);
}
}
Teach BBVectorize to combine, when possible, or discard metadata when fusing instructions. The present implementation handles only TBAA and FP metadata, discarding everything else. For debug metadata, the current behavior is maintained (the debug metadata associated with one of the instructions will be kept, discarding that attached to the other). This should address PR 13040. llvm-svn: 158606
2012-06-17 04:34:06 +08:00
// When the first instruction in each pair is cloned, it will inherit its
// parent's metadata. This metadata must be combined with that of the other
// instruction in a safe way.
void BBVectorize::combineMetadata(Instruction *K, const Instruction *J) {
SmallVector<std::pair<unsigned, MDNode*>, 4> Metadata;
K->getAllMetadataOtherThanDebugLoc(Metadata);
for (unsigned i = 0, n = Metadata.size(); i < n; ++i) {
unsigned Kind = Metadata[i].first;
MDNode *JMD = J->getMetadata(Kind);
MDNode *KMD = Metadata[i].second;
switch (Kind) {
default:
K->setMetadata(Kind, 0); // Remove unknown metadata
break;
case LLVMContext::MD_tbaa:
K->setMetadata(Kind, MDNode::getMostGenericTBAA(JMD, KMD));
break;
case LLVMContext::MD_fpmath:
K->setMetadata(Kind, MDNode::getMostGenericFPMath(JMD, KMD));
break;
}
}
}
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
// This function fuses the chosen instruction pairs into vector instructions,
// taking care preserve any needed scalar outputs and, then, it reorders the
// remaining instructions as needed (users of the first member of the pair
// need to be moved to after the location of the second member of the pair
// because the vector instruction is inserted in the location of the pair's
// second member).
void BBVectorize::fuseChosenPairs(BasicBlock &BB,
std::vector<Value *> &PairableInsts,
DenseMap<Value *, Value *> &ChosenPairs) {
LLVMContext& Context = BB.getContext();
// During the vectorization process, the order of the pairs to be fused
// could be flipped. So we'll add each pair, flipped, into the ChosenPairs
// list. After a pair is fused, the flipped pair is removed from the list.
std::vector<ValuePair> FlippedPairs;
FlippedPairs.reserve(ChosenPairs.size());
for (DenseMap<Value *, Value *>::iterator P = ChosenPairs.begin(),
E = ChosenPairs.end(); P != E; ++P)
FlippedPairs.push_back(ValuePair(P->second, P->first));
for (std::vector<ValuePair>::iterator P = FlippedPairs.begin(),
E = FlippedPairs.end(); P != E; ++P)
ChosenPairs.insert(*P);
std::multimap<Value *, Value *> LoadMoveSet;
collectLoadMoveSet(BB, PairableInsts, ChosenPairs, LoadMoveSet);
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
DenseSet<Value *> LowPtrInsts;
collectPtrInfo(PairableInsts, ChosenPairs, LowPtrInsts);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
DEBUG(dbgs() << "BBV: initial: \n" << BB << "\n");
for (BasicBlock::iterator PI = BB.getFirstInsertionPt(); PI != BB.end();) {
DenseMap<Value *, Value *>::iterator P = ChosenPairs.find(PI);
if (P == ChosenPairs.end()) {
++PI;
continue;
}
if (getDepthFactor(P->first) == 0) {
// These instructions are not really fused, but are tracked as though
// they are. Any case in which it would be interesting to fuse them
// will be taken care of by InstCombine.
--NumFusedOps;
++PI;
continue;
}
Instruction *I = cast<Instruction>(P->first),
*J = cast<Instruction>(P->second);
DEBUG(dbgs() << "BBV: fusing: " << *I <<
" <-> " << *J << "\n");
// Remove the pair and flipped pair from the list.
DenseMap<Value *, Value *>::iterator FP = ChosenPairs.find(P->second);
assert(FP != ChosenPairs.end() && "Flipped pair not found in list");
ChosenPairs.erase(FP);
ChosenPairs.erase(P);
if (!canMoveUsesOfIAfterJ(BB, LoadMoveSet, I, J)) {
DEBUG(dbgs() << "BBV: fusion of: " << *I <<
" <-> " << *J <<
" aborted because of non-trivial dependency cycle\n");
--NumFusedOps;
++PI;
continue;
}
Precompute SCEV pointer analysis prior to instruction fusion in BBVectorize. When both a load/store and its address computation are being vectorized, it can happen that the address-computation vectorization destroys SCEV's ability to analyize the relative pointer offsets. As a result (like with the aliasing analysis info), we need to precompute the necessary information prior to instruction fusing. This was found during stress testing (running through the test suite with a very low required chain length); unfortunately, I don't have a small test case. llvm-svn: 159332
2012-06-28 13:42:45 +08:00
bool FlipMemInputs = false;
if (isa<LoadInst>(I) || isa<StoreInst>(I))
FlipMemInputs = (LowPtrInsts.find(I) == LowPtrInsts.end());
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
unsigned NumOperands = I->getNumOperands();
SmallVector<Value *, 3> ReplacedOperands(NumOperands);
getReplacementInputsForPair(Context, I, J, ReplacedOperands,
FlipMemInputs);
// Make a copy of the original operation, change its type to the vector
// type and replace its operands with the vector operands.
Instruction *K = I->clone();
if (I->hasName()) K->takeName(I);
if (!isa<StoreInst>(K))
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
K->mutateType(getVecTypeForPair(I->getType(), J->getType()));
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
Teach BBVectorize to combine, when possible, or discard metadata when fusing instructions. The present implementation handles only TBAA and FP metadata, discarding everything else. For debug metadata, the current behavior is maintained (the debug metadata associated with one of the instructions will be kept, discarding that attached to the other). This should address PR 13040. llvm-svn: 158606
2012-06-17 04:34:06 +08:00
combineMetadata(K, J);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
for (unsigned o = 0; o < NumOperands; ++o)
K->setOperand(o, ReplacedOperands[o]);
// If we've flipped the memory inputs, make sure that we take the correct
// alignment.
if (FlipMemInputs) {
if (isa<StoreInst>(K))
cast<StoreInst>(K)->setAlignment(cast<StoreInst>(J)->getAlignment());
else
cast<LoadInst>(K)->setAlignment(cast<LoadInst>(J)->getAlignment());
}
K->insertAfter(J);
// Instruction insertion point:
Instruction *InsertionPt = K;
Instruction *K1 = 0, *K2 = 0;
replaceOutputsOfPair(Context, I, J, K, InsertionPt, K1, K2,
FlipMemInputs);
// The use tree of the first original instruction must be moved to after
// the location of the second instruction. The entire use tree of the
// first instruction is disjoint from the input tree of the second
// (by definition), and so commutes with it.
moveUsesOfIAfterJ(BB, LoadMoveSet, InsertionPt, I, J);
if (!isa<StoreInst>(I)) {
I->replaceAllUsesWith(K1);
J->replaceAllUsesWith(K2);
AA->replaceWithNewValue(I, K1);
AA->replaceWithNewValue(J, K2);
}
// Instructions that may read from memory may be in the load move set.
// Once an instruction is fused, we no longer need its move set, and so
// the values of the map never need to be updated. However, when a load
// is fused, we need to merge the entries from both instructions in the
// pair in case those instructions were in the move set of some other
// yet-to-be-fused pair. The loads in question are the keys of the map.
if (I->mayReadFromMemory()) {
std::vector<ValuePair> NewSetMembers;
VPIteratorPair IPairRange = LoadMoveSet.equal_range(I);
VPIteratorPair JPairRange = LoadMoveSet.equal_range(J);
for (std::multimap<Value *, Value *>::iterator N = IPairRange.first;
N != IPairRange.second; ++N)
NewSetMembers.push_back(ValuePair(K, N->second));
for (std::multimap<Value *, Value *>::iterator N = JPairRange.first;
N != JPairRange.second; ++N)
NewSetMembers.push_back(ValuePair(K, N->second));
for (std::vector<ValuePair>::iterator A = NewSetMembers.begin(),
AE = NewSetMembers.end(); A != AE; ++A)
LoadMoveSet.insert(*A);
}
// Before removing I, set the iterator to the next instruction.
PI = llvm::next(BasicBlock::iterator(I));
if (cast<Instruction>(PI) == J)
++PI;
SE->forgetValue(I);
SE->forgetValue(J);
I->eraseFromParent();
J->eraseFromParent();
}
DEBUG(dbgs() << "BBV: final: \n" << BB << "\n");
}
}
char BBVectorize::ID = 0;
static const char bb_vectorize_name[] = "Basic-Block Vectorization";
INITIALIZE_PASS_BEGIN(BBVectorize, BBV_NAME, bb_vectorize_name, false, false)
INITIALIZE_AG_DEPENDENCY(AliasAnalysis)
INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
INITIALIZE_PASS_END(BBVectorize, BBV_NAME, bb_vectorize_name, false, false)
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
BasicBlockPass *llvm::createBBVectorizePass(const VectorizeConfig &C) {
return new BBVectorize(C);
Add a basic-block autovectorization pass. This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure. Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser). llvm-svn: 149468
2012-02-01 11:51:43 +08:00
}
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
bool
llvm::vectorizeBasicBlock(Pass *P, BasicBlock &BB, const VectorizeConfig &C) {
BBVectorize BBVectorizer(P, C);
Add the function "vectorizeBasicBlock" which allow users vectorize a BasicBlock in other passes, e.g. we can call vectorizeBasicBlock in the loop unroll pass right after the loop is unrolled. llvm-svn: 154089
2012-04-05 16:05:16 +08:00
return BBVectorizer.vectorizeBB(BB);
}
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
//===----------------------------------------------------------------------===//
VectorizeConfig::VectorizeConfig() {
VectorBits = ::VectorBits;
Allow controlling vectorization of boolean values separately from other integer types. These are used as the result of comparisons, and often handled differently from larger integer types. llvm-svn: 159111
2012-06-24 21:28:01 +08:00
VectorizeBools = !::NoBools;
Refactor: Use positive field names in VectorizeConfig. llvm-svn: 154249
2012-04-07 11:56:23 +08:00
VectorizeInts = !::NoInts;
VectorizeFloats = !::NoFloats;
Enhance BBVectorize to more-properly handle pointer values and vectorize GEPs. llvm-svn: 154734
2012-04-14 15:32:43 +08:00
VectorizePointers = !::NoPointers;
Refactor: Use positive field names in VectorizeConfig. llvm-svn: 154249
2012-04-07 11:56:23 +08:00
VectorizeCasts = !::NoCasts;
VectorizeMath = !::NoMath;
VectorizeFMA = !::NoFMA;
Add support to BBVectorize for vectorizing selects. llvm-svn: 154700
2012-04-14 04:45:45 +08:00
VectorizeSelect = !::NoSelect;
Allow BBVectorize to fuse compare instructions. llvm-svn: 159088
2012-06-24 05:52:50 +08:00
VectorizeCmp = !::NoCmp;
Enhance BBVectorize to more-properly handle pointer values and vectorize GEPs. llvm-svn: 154734
2012-04-14 15:32:43 +08:00
VectorizeGEP = !::NoGEP;
Refactor: Use positive field names in VectorizeConfig. llvm-svn: 154249
2012-04-07 11:56:23 +08:00
VectorizeMemOps = !::NoMemOps;
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
AlignedOnly = ::AlignedOnly;
ReqChainDepth= ::ReqChainDepth;
SearchLimit = ::SearchLimit;
MaxCandPairsForCycleCheck = ::MaxCandPairsForCycleCheck;
SplatBreaksChain = ::SplatBreaksChain;
MaxInsts = ::MaxInsts;
MaxIter = ::MaxIter;
Allow BBVectorize to form non-2^n-length vectors. The original algorithm only used recursive pair fusion of equal-length types. This is now extended to allow pairing of any types that share the same underlying scalar type. Because we would still generally prefer the 2^n-length types, those are formed first. Then a second set of iterations form the non-2^n-length types. Also, a call to SimplifyInstructionsInBlock has been added after each pairing iteration. This takes care of DCE (and a few other things) that make the following iterations execute somewhat faster. For the same reason, some of the simple shuffle-combination cases are now handled internally. There is some additional refactoring work to be done, but I've had many requests for this feature, so additional refactoring will come soon in future commits (as will additional test cases). llvm-svn: 159330
2012-06-28 13:42:42 +08:00
Pow2LenOnly = ::Pow2LenOnly;
Introduce the VectorizeConfig class, with which we can control the behavior of the BBVectorizePass without using command line option. As pointed out by Hal, we can ask the TargetLoweringInfo for the architecture specific VectorizeConfig to perform vectorizing with architecture specific information. llvm-svn: 154096
2012-04-05 23:46:55 +08:00
NoMemOpBoost = ::NoMemOpBoost;
FastDep = ::FastDep;
}