llvm-project/llvm/lib/Transforms/Scalar/LoopLoadElimination.cpp

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LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
//===- LoopLoadElimination.cpp - Loop Load Elimination Pass ---------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This file implement a loop-aware load elimination pass.
//
// It uses LoopAccessAnalysis to identify loop-carried dependences with a
// distance of one between stores and loads. These form the candidates for the
// transformation. The source value of each store then propagated to the user
// of the corresponding load. This makes the load dead.
//
// The pass can also version the loop and add memchecks in order to prove that
// may-aliasing stores can't change the value in memory before it's read by the
// load.
//
//===----------------------------------------------------------------------===//
#include "llvm/ADT/Statistic.h"
#include "llvm/Analysis/LoopAccessAnalysis.h"
#include "llvm/Analysis/LoopInfo.h"
#include "llvm/Analysis/ScalarEvolutionExpander.h"
#include "llvm/IR/Dominators.h"
#include "llvm/IR/Module.h"
#include "llvm/Pass.h"
#include "llvm/Support/Debug.h"
#include "llvm/Transforms/Scalar.h"
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
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#include "llvm/Transforms/Utils/LoopVersioning.h"
#include <forward_list>
#define LLE_OPTION "loop-load-elim"
#define DEBUG_TYPE LLE_OPTION
using namespace llvm;
static cl::opt<unsigned> CheckPerElim(
"runtime-check-per-loop-load-elim", cl::Hidden,
cl::desc("Max number of memchecks allowed per eliminated load on average"),
cl::init(1));
static cl::opt<unsigned> LoadElimSCEVCheckThreshold(
"loop-load-elimination-scev-check-threshold", cl::init(8), cl::Hidden,
cl::desc("The maximum number of SCEV checks allowed for Loop "
"Load Elimination"));
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
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STATISTIC(NumLoopLoadEliminted, "Number of loads eliminated by LLE");
namespace {
/// \brief Represent a store-to-forwarding candidate.
struct StoreToLoadForwardingCandidate {
LoadInst *Load;
StoreInst *Store;
StoreToLoadForwardingCandidate(LoadInst *Load, StoreInst *Store)
: Load(Load), Store(Store) {}
/// \brief Return true if the dependence from the store to the load has a
/// distance of one. E.g. A[i+1] = A[i]
bool isDependenceDistanceOfOne(PredicatedScalarEvolution &PSE,
Loop *L) const {
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
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Value *LoadPtr = Load->getPointerOperand();
Value *StorePtr = Store->getPointerOperand();
Type *LoadPtrType = LoadPtr->getType();
Type *LoadType = LoadPtrType->getPointerElementType();
assert(LoadPtrType->getPointerAddressSpace() ==
StorePtr->getType()->getPointerAddressSpace() &&
LoadType == StorePtr->getType()->getPointerElementType() &&
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
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"Should be a known dependence");
// Currently we only support accesses with unit stride. FIXME: we should be
// able to handle non unit stirde as well as long as the stride is equal to
// the dependence distance.
if (getPtrStride(PSE, LoadPtr, L) != 1 ||
getPtrStride(PSE, StorePtr, L) != 1)
return false;
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
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auto &DL = Load->getParent()->getModule()->getDataLayout();
unsigned TypeByteSize = DL.getTypeAllocSize(const_cast<Type *>(LoadType));
auto *LoadPtrSCEV = cast<SCEVAddRecExpr>(PSE.getSCEV(LoadPtr));
auto *StorePtrSCEV = cast<SCEVAddRecExpr>(PSE.getSCEV(StorePtr));
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
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// We don't need to check non-wrapping here because forward/backward
// dependence wouldn't be valid if these weren't monotonic accesses.
auto *Dist = cast<SCEVConstant>(
PSE.getSE()->getMinusSCEV(StorePtrSCEV, LoadPtrSCEV));
const APInt &Val = Dist->getAPInt();
return Val == TypeByteSize;
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
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}
Value *getLoadPtr() const { return Load->getPointerOperand(); }
#ifndef NDEBUG
friend raw_ostream &operator<<(raw_ostream &OS,
const StoreToLoadForwardingCandidate &Cand) {
OS << *Cand.Store << " -->\n";
OS.indent(2) << *Cand.Load << "\n";
return OS;
}
#endif
};
/// \brief Check if the store dominates all latches, so as long as there is no
/// intervening store this value will be loaded in the next iteration.
bool doesStoreDominatesAllLatches(BasicBlock *StoreBlock, Loop *L,
DominatorTree *DT) {
SmallVector<BasicBlock *, 8> Latches;
L->getLoopLatches(Latches);
return std::all_of(Latches.begin(), Latches.end(),
[&](const BasicBlock *Latch) {
return DT->dominates(StoreBlock, Latch);
});
}
/// \brief Return true if the load is not executed on all paths in the loop.
static bool isLoadConditional(LoadInst *Load, Loop *L) {
return Load->getParent() != L->getHeader();
}
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
/// \brief The per-loop class that does most of the work.
class LoadEliminationForLoop {
public:
LoadEliminationForLoop(Loop *L, LoopInfo *LI, const LoopAccessInfo &LAI,
DominatorTree *DT)
: L(L), LI(LI), LAI(LAI), DT(DT), PSE(LAI.getPSE()) {}
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
/// \brief Look through the loop-carried and loop-independent dependences in
/// this loop and find store->load dependences.
///
/// Note that no candidate is returned if LAA has failed to analyze the loop
/// (e.g. if it's not bottom-tested, contains volatile memops, etc.)
std::forward_list<StoreToLoadForwardingCandidate>
findStoreToLoadDependences(const LoopAccessInfo &LAI) {
std::forward_list<StoreToLoadForwardingCandidate> Candidates;
const auto *Deps = LAI.getDepChecker().getDependences();
if (!Deps)
return Candidates;
// Find store->load dependences (consequently true dep). Both lexically
// forward and backward dependences qualify. Disqualify loads that have
// other unknown dependences.
SmallSet<Instruction *, 4> LoadsWithUnknownDepedence;
for (const auto &Dep : *Deps) {
Instruction *Source = Dep.getSource(LAI);
Instruction *Destination = Dep.getDestination(LAI);
if (Dep.Type == MemoryDepChecker::Dependence::Unknown) {
if (isa<LoadInst>(Source))
LoadsWithUnknownDepedence.insert(Source);
if (isa<LoadInst>(Destination))
LoadsWithUnknownDepedence.insert(Destination);
continue;
}
if (Dep.isBackward())
// Note that the designations source and destination follow the program
// order, i.e. source is always first. (The direction is given by the
// DepType.)
std::swap(Source, Destination);
else
assert(Dep.isForward() && "Needs to be a forward dependence");
auto *Store = dyn_cast<StoreInst>(Source);
if (!Store)
continue;
auto *Load = dyn_cast<LoadInst>(Destination);
if (!Load)
continue;
// Only progagate the value if they are of the same type.
if (Store->getPointerOperand()->getType() !=
Load->getPointerOperand()->getType())
continue;
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
Candidates.emplace_front(Load, Store);
}
if (!LoadsWithUnknownDepedence.empty())
Candidates.remove_if([&](const StoreToLoadForwardingCandidate &C) {
return LoadsWithUnknownDepedence.count(C.Load);
});
return Candidates;
}
/// \brief Return the index of the instruction according to program order.
unsigned getInstrIndex(Instruction *Inst) {
auto I = InstOrder.find(Inst);
assert(I != InstOrder.end() && "No index for instruction");
return I->second;
}
/// \brief If a load has multiple candidates associated (i.e. different
/// stores), it means that it could be forwarding from multiple stores
/// depending on control flow. Remove these candidates.
///
/// Here, we rely on LAA to include the relevant loop-independent dependences.
/// LAA is known to omit these in the very simple case when the read and the
/// write within an alias set always takes place using the *same* pointer.
///
/// However, we know that this is not the case here, i.e. we can rely on LAA
/// to provide us with loop-independent dependences for the cases we're
/// interested. Consider the case for example where a loop-independent
/// dependece S1->S2 invalidates the forwarding S3->S2.
///
/// A[i] = ... (S1)
/// ... = A[i] (S2)
/// A[i+1] = ... (S3)
///
/// LAA will perform dependence analysis here because there are two
/// *different* pointers involved in the same alias set (&A[i] and &A[i+1]).
void removeDependencesFromMultipleStores(
std::forward_list<StoreToLoadForwardingCandidate> &Candidates) {
// If Store is nullptr it means that we have multiple stores forwarding to
// this store.
typedef DenseMap<LoadInst *, const StoreToLoadForwardingCandidate *>
LoadToSingleCandT;
LoadToSingleCandT LoadToSingleCand;
for (const auto &Cand : Candidates) {
bool NewElt;
LoadToSingleCandT::iterator Iter;
std::tie(Iter, NewElt) =
LoadToSingleCand.insert(std::make_pair(Cand.Load, &Cand));
if (!NewElt) {
const StoreToLoadForwardingCandidate *&OtherCand = Iter->second;
// Already multiple stores forward to this load.
if (OtherCand == nullptr)
continue;
2016-03-01 07:21:12 +08:00
// Handle the very basic case when the two stores are in the same block
// so deciding which one forwards is easy. The later one forwards as
// long as they both have a dependence distance of one to the load.
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
if (Cand.Store->getParent() == OtherCand->Store->getParent() &&
Cand.isDependenceDistanceOfOne(PSE, L) &&
OtherCand->isDependenceDistanceOfOne(PSE, L)) {
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
// They are in the same block, the later one will forward to the load.
if (getInstrIndex(OtherCand->Store) < getInstrIndex(Cand.Store))
OtherCand = &Cand;
} else
OtherCand = nullptr;
}
}
Candidates.remove_if([&](const StoreToLoadForwardingCandidate &Cand) {
if (LoadToSingleCand[Cand.Load] != &Cand) {
DEBUG(dbgs() << "Removing from candidates: \n" << Cand
<< " The load may have multiple stores forwarding to "
<< "it\n");
return true;
}
return false;
});
}
/// \brief Given two pointers operations by their RuntimePointerChecking
/// indices, return true if they require an alias check.
///
/// We need a check if one is a pointer for a candidate load and the other is
/// a pointer for a possibly intervening store.
bool needsChecking(unsigned PtrIdx1, unsigned PtrIdx2,
const SmallSet<Value *, 4> &PtrsWrittenOnFwdingPath,
const std::set<Value *> &CandLoadPtrs) {
Value *Ptr1 =
LAI.getRuntimePointerChecking()->getPointerInfo(PtrIdx1).PointerValue;
Value *Ptr2 =
LAI.getRuntimePointerChecking()->getPointerInfo(PtrIdx2).PointerValue;
return ((PtrsWrittenOnFwdingPath.count(Ptr1) && CandLoadPtrs.count(Ptr2)) ||
(PtrsWrittenOnFwdingPath.count(Ptr2) && CandLoadPtrs.count(Ptr1)));
}
/// \brief Return pointers that are possibly written to on the path from a
/// forwarding store to a load.
///
/// These pointers need to be alias-checked against the forwarding candidates.
SmallSet<Value *, 4> findPointersWrittenOnForwardingPath(
const SmallVectorImpl<StoreToLoadForwardingCandidate> &Candidates) {
// From FirstStore to LastLoad neither of the elimination candidate loads
// should overlap with any of the stores.
//
// E.g.:
//
// st1 C[i]
// ld1 B[i] <-------,
// ld0 A[i] <----, | * LastLoad
// ... | |
// st2 E[i] | |
// st3 B[i+1] -- | -' * FirstStore
// st0 A[i+1] ---'
// st4 D[i]
//
// st0 forwards to ld0 if the accesses in st4 and st1 don't overlap with
// ld0.
LoadInst *LastLoad =
std::max_element(Candidates.begin(), Candidates.end(),
[&](const StoreToLoadForwardingCandidate &A,
const StoreToLoadForwardingCandidate &B) {
return getInstrIndex(A.Load) < getInstrIndex(B.Load);
})
->Load;
StoreInst *FirstStore =
std::min_element(Candidates.begin(), Candidates.end(),
[&](const StoreToLoadForwardingCandidate &A,
const StoreToLoadForwardingCandidate &B) {
return getInstrIndex(A.Store) <
getInstrIndex(B.Store);
})
->Store;
// We're looking for stores after the first forwarding store until the end
// of the loop, then from the beginning of the loop until the last
// forwarded-to load. Collect the pointer for the stores.
SmallSet<Value *, 4> PtrsWrittenOnFwdingPath;
auto InsertStorePtr = [&](Instruction *I) {
if (auto *S = dyn_cast<StoreInst>(I))
PtrsWrittenOnFwdingPath.insert(S->getPointerOperand());
};
const auto &MemInstrs = LAI.getDepChecker().getMemoryInstructions();
std::for_each(MemInstrs.begin() + getInstrIndex(FirstStore) + 1,
MemInstrs.end(), InsertStorePtr);
std::for_each(MemInstrs.begin(), &MemInstrs[getInstrIndex(LastLoad)],
InsertStorePtr);
return PtrsWrittenOnFwdingPath;
}
/// \brief Determine the pointer alias checks to prove that there are no
/// intervening stores.
SmallVector<RuntimePointerChecking::PointerCheck, 4> collectMemchecks(
const SmallVectorImpl<StoreToLoadForwardingCandidate> &Candidates) {
SmallSet<Value *, 4> PtrsWrittenOnFwdingPath =
findPointersWrittenOnForwardingPath(Candidates);
// Collect the pointers of the candidate loads.
// FIXME: SmallSet does not work with std::inserter.
std::set<Value *> CandLoadPtrs;
std::transform(Candidates.begin(), Candidates.end(),
std::inserter(CandLoadPtrs, CandLoadPtrs.begin()),
std::mem_fn(&StoreToLoadForwardingCandidate::getLoadPtr));
const auto &AllChecks = LAI.getRuntimePointerChecking()->getChecks();
SmallVector<RuntimePointerChecking::PointerCheck, 4> Checks;
std::copy_if(AllChecks.begin(), AllChecks.end(), std::back_inserter(Checks),
[&](const RuntimePointerChecking::PointerCheck &Check) {
for (auto PtrIdx1 : Check.first->Members)
for (auto PtrIdx2 : Check.second->Members)
if (needsChecking(PtrIdx1, PtrIdx2,
PtrsWrittenOnFwdingPath, CandLoadPtrs))
return true;
return false;
});
DEBUG(dbgs() << "\nPointer Checks (count: " << Checks.size() << "):\n");
DEBUG(LAI.getRuntimePointerChecking()->printChecks(dbgs(), Checks));
return Checks;
}
/// \brief Perform the transformation for a candidate.
void
propagateStoredValueToLoadUsers(const StoreToLoadForwardingCandidate &Cand,
SCEVExpander &SEE) {
//
// loop:
// %x = load %gep_i
// = ... %x
// store %y, %gep_i_plus_1
//
// =>
//
// ph:
// %x.initial = load %gep_0
// loop:
// %x.storeforward = phi [%x.initial, %ph] [%y, %loop]
// %x = load %gep_i <---- now dead
// = ... %x.storeforward
// store %y, %gep_i_plus_1
Value *Ptr = Cand.Load->getPointerOperand();
auto *PtrSCEV = cast<SCEVAddRecExpr>(PSE.getSCEV(Ptr));
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
auto *PH = L->getLoopPreheader();
Value *InitialPtr = SEE.expandCodeFor(PtrSCEV->getStart(), Ptr->getType(),
PH->getTerminator());
Value *Initial =
new LoadInst(InitialPtr, "load_initial", PH->getTerminator());
PHINode *PHI = PHINode::Create(Initial->getType(), 2, "store_forwarded",
&L->getHeader()->front());
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
PHI->addIncoming(Initial, PH);
PHI->addIncoming(Cand.Store->getOperand(0), L->getLoopLatch());
Cand.Load->replaceAllUsesWith(PHI);
}
/// \brief Top-level driver for each loop: find store->load forwarding
/// candidates, add run-time checks and perform transformation.
bool processLoop() {
DEBUG(dbgs() << "\nIn \"" << L->getHeader()->getParent()->getName()
<< "\" checking " << *L << "\n");
// Look for store-to-load forwarding cases across the
// backedge. E.g.:
//
// loop:
// %x = load %gep_i
// = ... %x
// store %y, %gep_i_plus_1
//
// =>
//
// ph:
// %x.initial = load %gep_0
// loop:
// %x.storeforward = phi [%x.initial, %ph] [%y, %loop]
// %x = load %gep_i <---- now dead
// = ... %x.storeforward
// store %y, %gep_i_plus_1
// First start with store->load dependences.
auto StoreToLoadDependences = findStoreToLoadDependences(LAI);
if (StoreToLoadDependences.empty())
return false;
// Generate an index for each load and store according to the original
// program order. This will be used later.
InstOrder = LAI.getDepChecker().generateInstructionOrderMap();
// To keep things simple for now, remove those where the load is potentially
// fed by multiple stores.
removeDependencesFromMultipleStores(StoreToLoadDependences);
if (StoreToLoadDependences.empty())
return false;
// Filter the candidates further.
SmallVector<StoreToLoadForwardingCandidate, 4> Candidates;
unsigned NumForwarding = 0;
for (const StoreToLoadForwardingCandidate Cand : StoreToLoadDependences) {
DEBUG(dbgs() << "Candidate " << Cand);
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
// Make sure that the stored values is available everywhere in the loop in
// the next iteration.
if (!doesStoreDominatesAllLatches(Cand.Store->getParent(), L, DT))
continue;
// If the load is conditional we can't hoist its 0-iteration instance to
// the preheader because that would make it unconditional. Thus we would
// access a memory location that the original loop did not access.
if (isLoadConditional(Cand.Load, L))
continue;
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
// Check whether the SCEV difference is the same as the induction step,
// thus we load the value in the next iteration.
if (!Cand.isDependenceDistanceOfOne(PSE, L))
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
continue;
++NumForwarding;
DEBUG(dbgs()
<< NumForwarding
<< ". Valid store-to-load forwarding across the loop backedge\n");
Candidates.push_back(Cand);
}
if (Candidates.empty())
return false;
// Check intervening may-alias stores. These need runtime checks for alias
// disambiguation.
SmallVector<RuntimePointerChecking::PointerCheck, 4> Checks =
collectMemchecks(Candidates);
// Too many checks are likely to outweigh the benefits of forwarding.
if (Checks.size() > Candidates.size() * CheckPerElim) {
DEBUG(dbgs() << "Too many run-time checks needed.\n");
return false;
}
if (LAI.getPSE().getUnionPredicate().getComplexity() >
LoadElimSCEVCheckThreshold) {
DEBUG(dbgs() << "Too many SCEV run-time checks needed.\n");
return false;
}
if (!Checks.empty() || !LAI.getPSE().getUnionPredicate().isAlwaysTrue()) {
if (L->getHeader()->getParent()->optForSize()) {
DEBUG(dbgs() << "Versioning is needed but not allowed when optimizing "
"for size.\n");
return false;
}
// Point of no-return, start the transformation. First, version the loop
// if necessary.
LoopVersioning LV(LAI, L, LI, DT, PSE.getSE(), false);
LV.setAliasChecks(std::move(Checks));
LV.setSCEVChecks(LAI.getPSE().getUnionPredicate());
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
LV.versionLoop();
}
// Next, propagate the value stored by the store to the users of the load.
// Also for the first iteration, generate the initial value of the load.
SCEVExpander SEE(*PSE.getSE(), L->getHeader()->getModule()->getDataLayout(),
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
"storeforward");
for (const auto &Cand : Candidates)
propagateStoredValueToLoadUsers(Cand, SEE);
NumLoopLoadEliminted += NumForwarding;
return true;
}
private:
Loop *L;
/// \brief Maps the load/store instructions to their index according to
/// program order.
DenseMap<Instruction *, unsigned> InstOrder;
// Analyses used.
LoopInfo *LI;
const LoopAccessInfo &LAI;
DominatorTree *DT;
PredicatedScalarEvolution PSE;
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
};
/// \brief The pass. Most of the work is delegated to the per-loop
/// LoadEliminationForLoop class.
class LoopLoadElimination : public FunctionPass {
public:
LoopLoadElimination() : FunctionPass(ID) {
initializeLoopLoadEliminationPass(*PassRegistry::getPassRegistry());
}
bool runOnFunction(Function &F) override {
if (skipFunction(F))
return false;
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
auto *LAA = &getAnalysis<LoopAccessLegacyAnalysis>();
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
// Build up a worklist of inner-loops to vectorize. This is necessary as the
// act of distributing a loop creates new loops and can invalidate iterators
// across the loops.
SmallVector<Loop *, 8> Worklist;
for (Loop *TopLevelLoop : *LI)
for (Loop *L : depth_first(TopLevelLoop))
// We only handle inner-most loops.
if (L->empty())
Worklist.push_back(L);
// Now walk the identified inner loops.
bool Changed = false;
for (Loop *L : Worklist) {
const LoopAccessInfo &LAI = LAA->getInfo(L);
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
// The actual work is performed by LoadEliminationForLoop.
LoadEliminationForLoop LEL(L, LI, LAI, DT);
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
Changed |= LEL.processLoop();
}
// Process each loop nest in the function.
return Changed;
}
void getAnalysisUsage(AnalysisUsage &AU) const override {
AU.addRequiredID(LoopSimplifyID);
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
AU.addRequired<LoopInfoWrapperPass>();
AU.addPreserved<LoopInfoWrapperPass>();
AU.addRequired<LoopAccessLegacyAnalysis>();
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
AU.addRequired<ScalarEvolutionWrapperPass>();
AU.addRequired<DominatorTreeWrapperPass>();
AU.addPreserved<DominatorTreeWrapperPass>();
}
static char ID;
};
}
char LoopLoadElimination::ID;
static const char LLE_name[] = "Loop Load Elimination";
INITIALIZE_PASS_BEGIN(LoopLoadElimination, LLE_OPTION, LLE_name, false, false)
INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(LoopAccessLegacyAnalysis)
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass)
INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
LLE 6/6: Add LoopLoadElimination pass Summary: The goal of this pass is to perform store-to-load forwarding across the backedge of a loop. E.g.: for (i) A[i + 1] = A[i] + B[i] => T = A[0] for (i) T = T + B[i] A[i + 1] = T The pass relies on loop dependence analysis via LoopAccessAnalisys to find opportunities of loop-carried dependences with a distance of one between a store and a load. Since it's using LoopAccessAnalysis, it was easy to also add support for versioning away may-aliasing intervening stores that would otherwise prevent this transformation. This optimization is also performed by Load-PRE in GVN without the option of multi-versioning. As was discussed with Daniel Berlin in http://reviews.llvm.org/D9548, this is inferior to a more loop-aware solution applied here. Hopefully, we will be able to remove some complexity from GVN/MemorySSA as a consequence. In the long run, we may want to extend this pass (or create a new one if there is little overlap) to also eliminate loop-indepedent redundant loads and store that *require* versioning due to may-aliasing intervening stores/loads. I have some motivating cases for store elimination. My plan right now is to wait for MemorySSA to come online first rather than using memdep for this. The main motiviation for this pass is the 456.hmmer loop in SPECint2006 where after distributing the original loop and vectorizing the top part, we are left with the critical path exposed in the bottom loop. Being able to promote the memory dependence into a register depedence (even though the HW does perform store-to-load fowarding as well) results in a major gain (~20%). This gain also transfers over to x86: it's around 8-10%. Right now the pass is off by default and can be enabled with -enable-loop-load-elim. On the LNT testsuite, there are two performance changes (negative number -> improvement): 1. -28% in Polybench/linear-algebra/solvers/dynprog: the length of the critical paths is reduced 2. +2% in Polybench/stencils/adi: Unfortunately, I couldn't reproduce this outside of LNT The pass is scheduled after the loop vectorizer (which is after loop distribution). The rational is to try to reuse LAA state, rather than recomputing it. The order between LV and LLE is not critical because normally LV does not touch scalar st->ld forwarding cases where vectorizing would inhibit the CPU's st->ld forwarding to kick in. LoopLoadElimination requires LAA to provide the full set of dependences (including forward dependences). LAA is known to omit loop-independent dependences in certain situations. The big comment before removeDependencesFromMultipleStores explains why this should not occur for the cases that we're interested in. Reviewers: dberlin, hfinkel Subscribers: junbuml, dberlin, mssimpso, rengolin, sanjoy, llvm-commits Differential Revision: http://reviews.llvm.org/D13259 llvm-svn: 252017
2015-11-04 07:50:08 +08:00
INITIALIZE_PASS_END(LoopLoadElimination, LLE_OPTION, LLE_name, false, false)
namespace llvm {
FunctionPass *createLoopLoadEliminationPass() {
return new LoopLoadElimination();
}
}