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

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//===-- LoopIdiomRecognize.cpp - Loop idiom recognition -------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This pass implements an idiom recognizer that transforms simple loops into a
// non-loop form. In cases that this kicks in, it can be a significant
// performance win.
//
//===----------------------------------------------------------------------===//
//
// TODO List:
//
// Future loop memory idioms to recognize:
// memcmp, memmove, strlen, etc.
// Future floating point idioms to recognize in -ffast-math mode:
// fpowi
// Future integer operation idioms to recognize:
// ctpop, ctlz, cttz
//
// Beware that isel's default lowering for ctpop is highly inefficient for
// i64 and larger types when i64 is legal and the value has few bits set. It
// would be good to enhance isel to emit a loop for ctpop in this case.
//
// We should enhance the memset/memcpy recognition to handle multiple stores in
// the loop. This would handle things like:
// void foo(_Complex float *P)
// for (i) { __real__(*P) = 0; __imag__(*P) = 0; }
//
// This could recognize common matrix multiplies and dot product idioms and
// replace them with calls to BLAS (if linked in??).
//
//===----------------------------------------------------------------------===//
#include "llvm/Transforms/Scalar.h"
#include "llvm/ADT/Statistic.h"
#include "llvm/Analysis/AliasAnalysis.h"
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-10 01:55:00 +08:00
#include "llvm/Analysis/BasicAliasAnalysis.h"
#include "llvm/Analysis/GlobalsModRef.h"
#include "llvm/Analysis/LoopPass.h"
#include "llvm/Analysis/ScalarEvolutionExpander.h"
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-10 01:55:00 +08:00
#include "llvm/Analysis/ScalarEvolutionAliasAnalysis.h"
#include "llvm/Analysis/ScalarEvolutionExpressions.h"
#include "llvm/Analysis/TargetLibraryInfo.h"
#include "llvm/Analysis/TargetTransformInfo.h"
#include "llvm/Analysis/ValueTracking.h"
#include "llvm/IR/DataLayout.h"
#include "llvm/IR/Dominators.h"
#include "llvm/IR/IRBuilder.h"
#include "llvm/IR/IntrinsicInst.h"
#include "llvm/IR/Module.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/Utils/Local.h"
using namespace llvm;
#define DEBUG_TYPE "loop-idiom"
STATISTIC(NumMemSet, "Number of memset's formed from loop stores");
STATISTIC(NumMemCpy, "Number of memcpy's formed from loop load+stores");
namespace {
class LoopIdiomRecognize : public LoopPass {
Loop *CurLoop;
AliasAnalysis *AA;
DominatorTree *DT;
LoopInfo *LI;
ScalarEvolution *SE;
TargetLibraryInfo *TLI;
const TargetTransformInfo *TTI;
public:
static char ID;
explicit LoopIdiomRecognize() : LoopPass(ID) {
initializeLoopIdiomRecognizePass(*PassRegistry::getPassRegistry());
}
bool runOnLoop(Loop *L, LPPassManager &LPM) override;
/// This transformation requires natural loop information & requires that
/// loop preheaders be inserted into the CFG.
///
void getAnalysisUsage(AnalysisUsage &AU) const override {
AU.addRequired<LoopInfoWrapperPass>();
AU.addPreserved<LoopInfoWrapperPass>();
AU.addRequiredID(LoopSimplifyID);
AU.addPreservedID(LoopSimplifyID);
AU.addRequiredID(LCSSAID);
AU.addPreservedID(LCSSAID);
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-10 01:55:00 +08:00
AU.addRequired<AAResultsWrapperPass>();
AU.addPreserved<AAResultsWrapperPass>();
[PM] Port ScalarEvolution to the new pass manager. This change makes ScalarEvolution a stand-alone object and just produces one from a pass as needed. Making this work well requires making the object movable, using references instead of overwritten pointers in a number of places, and other refactorings. I've also wired it up to the new pass manager and added a RUN line to a test to exercise it under the new pass manager. This includes basic printing support much like with other analyses. But there is a big and somewhat scary change here. Prior to this patch ScalarEvolution was never *actually* invalidated!!! Re-running the pass just re-wired up the various other analyses and didn't remove any of the existing entries in the SCEV caches or clear out anything at all. This might seem OK as everything in SCEV that can uses ValueHandles to track updates to the values that serve as SCEV keys. However, this still means that as we ran SCEV over each function in the module, we kept accumulating more and more SCEVs into the cache. At the end, we would have a SCEV cache with every value that we ever needed a SCEV for in the entire module!!! Yowzers. The releaseMemory routine would dump all of this, but that isn't realy called during normal runs of the pipeline as far as I can see. To make matters worse, there *is* actually a key that we don't update with value handles -- there is a map keyed off of Loop*s. Because LoopInfo *does* release its memory from run to run, it is entirely possible to run SCEV over one function, then over another function, and then lookup a Loop* from the second function but find an entry inserted for the first function! Ouch. To make matters still worse, there are plenty of updates that *don't* trip a value handle. It seems incredibly unlikely that today GVN or another pass that invalidates SCEV can update values in *just* such a way that a subsequent run of SCEV will incorrectly find lookups in a cache, but it is theoretically possible and would be a nightmare to debug. With this refactoring, I've fixed all this by actually destroying and recreating the ScalarEvolution object from run to run. Technically, this could increase the amount of malloc traffic we see, but then again it is also technically correct. ;] I don't actually think we're suffering from tons of malloc traffic from SCEV because if we were, the fact that we never clear the memory would seem more likely to have come up as an actual problem before now. So, I've made the simple fix here. If in fact there are serious issues with too much allocation and deallocation, I can work on a clever fix that preserves the allocations (while clearing the data) between each run, but I'd prefer to do that kind of optimization with a test case / benchmark that shows why we need such cleverness (and that can test that we actually make it faster). It's possible that this will make some things faster by making the SCEV caches have higher locality (due to being significantly smaller) so until there is a clear benchmark, I think the simple change is best. Differential Revision: http://reviews.llvm.org/D12063 llvm-svn: 245193
2015-08-17 10:08:17 +08:00
AU.addRequired<ScalarEvolutionWrapperPass>();
AU.addPreserved<ScalarEvolutionWrapperPass>();
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-10 01:55:00 +08:00
AU.addPreserved<SCEVAAWrapperPass>();
AU.addRequired<DominatorTreeWrapperPass>();
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-10 01:55:00 +08:00
AU.addPreserved<DominatorTreeWrapperPass>();
AU.addRequired<TargetLibraryInfoWrapperPass>();
AU.addRequired<TargetTransformInfoWrapperPass>();
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-10 01:55:00 +08:00
AU.addPreserved<BasicAAWrapperPass>();
AU.addPreserved<GlobalsAAWrapperPass>();
}
private:
/// \name Countable Loop Idiom Handling
/// @{
bool runOnCountableLoop();
bool runOnLoopBlock(BasicBlock *BB, const SCEV *BECount,
SmallVectorImpl<BasicBlock *> &ExitBlocks);
bool processLoopStore(StoreInst *SI, const SCEV *BECount);
bool processLoopMemSet(MemSetInst *MSI, const SCEV *BECount);
bool processLoopStridedStore(Value *DestPtr, unsigned StoreSize,
unsigned StoreAlignment, Value *SplatValue,
Instruction *TheStore, const SCEVAddRecExpr *Ev,
const SCEV *BECount, bool NegStride);
bool processLoopStoreOfLoopLoad(StoreInst *SI, unsigned StoreSize,
const SCEVAddRecExpr *StoreEv,
const SCEVAddRecExpr *LoadEv,
const SCEV *BECount);
/// @}
/// \name Noncountable Loop Idiom Handling
/// @{
bool runOnNoncountableLoop();
bool recognizePopcount();
void transformLoopToPopcount(BasicBlock *PreCondBB, Instruction *CntInst,
PHINode *CntPhi, Value *Var);
/// @}
};
} // End anonymous namespace.
char LoopIdiomRecognize::ID = 0;
INITIALIZE_PASS_BEGIN(LoopIdiomRecognize, "loop-idiom", "Recognize loop idioms",
false, false)
INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
INITIALIZE_PASS_DEPENDENCY(LCSSA)
[PM] Port ScalarEvolution to the new pass manager. This change makes ScalarEvolution a stand-alone object and just produces one from a pass as needed. Making this work well requires making the object movable, using references instead of overwritten pointers in a number of places, and other refactorings. I've also wired it up to the new pass manager and added a RUN line to a test to exercise it under the new pass manager. This includes basic printing support much like with other analyses. But there is a big and somewhat scary change here. Prior to this patch ScalarEvolution was never *actually* invalidated!!! Re-running the pass just re-wired up the various other analyses and didn't remove any of the existing entries in the SCEV caches or clear out anything at all. This might seem OK as everything in SCEV that can uses ValueHandles to track updates to the values that serve as SCEV keys. However, this still means that as we ran SCEV over each function in the module, we kept accumulating more and more SCEVs into the cache. At the end, we would have a SCEV cache with every value that we ever needed a SCEV for in the entire module!!! Yowzers. The releaseMemory routine would dump all of this, but that isn't realy called during normal runs of the pipeline as far as I can see. To make matters worse, there *is* actually a key that we don't update with value handles -- there is a map keyed off of Loop*s. Because LoopInfo *does* release its memory from run to run, it is entirely possible to run SCEV over one function, then over another function, and then lookup a Loop* from the second function but find an entry inserted for the first function! Ouch. To make matters still worse, there are plenty of updates that *don't* trip a value handle. It seems incredibly unlikely that today GVN or another pass that invalidates SCEV can update values in *just* such a way that a subsequent run of SCEV will incorrectly find lookups in a cache, but it is theoretically possible and would be a nightmare to debug. With this refactoring, I've fixed all this by actually destroying and recreating the ScalarEvolution object from run to run. Technically, this could increase the amount of malloc traffic we see, but then again it is also technically correct. ;] I don't actually think we're suffering from tons of malloc traffic from SCEV because if we were, the fact that we never clear the memory would seem more likely to have come up as an actual problem before now. So, I've made the simple fix here. If in fact there are serious issues with too much allocation and deallocation, I can work on a clever fix that preserves the allocations (while clearing the data) between each run, but I'd prefer to do that kind of optimization with a test case / benchmark that shows why we need such cleverness (and that can test that we actually make it faster). It's possible that this will make some things faster by making the SCEV caches have higher locality (due to being significantly smaller) so until there is a clear benchmark, I think the simple change is best. Differential Revision: http://reviews.llvm.org/D12063 llvm-svn: 245193
2015-08-17 10:08:17 +08:00
INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass)
INITIALIZE_PASS_DEPENDENCY(TargetLibraryInfoWrapperPass)
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-10 01:55:00 +08:00
INITIALIZE_PASS_DEPENDENCY(BasicAAWrapperPass)
INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass)
INITIALIZE_PASS_DEPENDENCY(GlobalsAAWrapperPass)
INITIALIZE_PASS_DEPENDENCY(SCEVAAWrapperPass)
[PM] Change the core design of the TTI analysis to use a polymorphic type erased interface and a single analysis pass rather than an extremely complex analysis group. The end result is that the TTI analysis can contain a type erased implementation that supports the polymorphic TTI interface. We can build one from a target-specific implementation or from a dummy one in the IR. I've also factored all of the code into "mix-in"-able base classes, including CRTP base classes to facilitate calling back up to the most specialized form when delegating horizontally across the surface. These aren't as clean as I would like and I'm planning to work on cleaning some of this up, but I wanted to start by putting into the right form. There are a number of reasons for this change, and this particular design. The first and foremost reason is that an analysis group is complete overkill, and the chaining delegation strategy was so opaque, confusing, and high overhead that TTI was suffering greatly for it. Several of the TTI functions had failed to be implemented in all places because of the chaining-based delegation making there be no checking of this. A few other functions were implemented with incorrect delegation. The message to me was very clear working on this -- the delegation and analysis group structure was too confusing to be useful here. The other reason of course is that this is *much* more natural fit for the new pass manager. This will lay the ground work for a type-erased per-function info object that can look up the correct subtarget and even cache it. Yet another benefit is that this will significantly simplify the interaction of the pass managers and the TargetMachine. See the future work below. The downside of this change is that it is very, very verbose. I'm going to work to improve that, but it is somewhat an implementation necessity in C++ to do type erasure. =/ I discussed this design really extensively with Eric and Hal prior to going down this path, and afterward showed them the result. No one was really thrilled with it, but there doesn't seem to be a substantially better alternative. Using a base class and virtual method dispatch would make the code much shorter, but as discussed in the update to the programmer's manual and elsewhere, a polymorphic interface feels like the more principled approach even if this is perhaps the least compelling example of it. ;] Ultimately, there is still a lot more to be done here, but this was the huge chunk that I couldn't really split things out of because this was the interface change to TTI. I've tried to minimize all the other parts of this. The follow up work should include at least: 1) Improving the TargetMachine interface by having it directly return a TTI object. Because we have a non-pass object with value semantics and an internal type erasure mechanism, we can narrow the interface of the TargetMachine to *just* do what we need: build and return a TTI object that we can then insert into the pass pipeline. 2) Make the TTI object be fully specialized for a particular function. This will include splitting off a minimal form of it which is sufficient for the inliner and the old pass manager. 3) Add a new pass manager analysis which produces TTI objects from the target machine for each function. This may actually be done as part of #2 in order to use the new analysis to implement #2. 4) Work on narrowing the API between TTI and the targets so that it is easier to understand and less verbose to type erase. 5) Work on narrowing the API between TTI and its clients so that it is easier to understand and less verbose to forward. 6) Try to improve the CRTP-based delegation. I feel like this code is just a bit messy and exacerbating the complexity of implementing the TTI in each target. Many thanks to Eric and Hal for their help here. I ended up blocked on this somewhat more abruptly than I expected, and so I appreciate getting it sorted out very quickly. Differential Revision: http://reviews.llvm.org/D7293 llvm-svn: 227669
2015-01-31 11:43:40 +08:00
INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass)
INITIALIZE_PASS_END(LoopIdiomRecognize, "loop-idiom", "Recognize loop idioms",
false, false)
Pass *llvm::createLoopIdiomPass() { return new LoopIdiomRecognize(); }
/// deleteDeadInstruction - Delete this instruction. Before we do, go through
/// and zero out all the operands of this instruction. If any of them become
/// dead, delete them and the computation tree that feeds them.
///
static void deleteDeadInstruction(Instruction *I,
const TargetLibraryInfo *TLI) {
SmallVector<Value *, 16> Operands(I->value_op_begin(), I->value_op_end());
I->replaceAllUsesWith(UndefValue::get(I->getType()));
I->eraseFromParent();
for (Value *Op : Operands)
RecursivelyDeleteTriviallyDeadInstructions(Op, TLI);
}
//===----------------------------------------------------------------------===//
//
// Implementation of LoopIdiomRecognize
//
//===----------------------------------------------------------------------===//
bool LoopIdiomRecognize::runOnLoop(Loop *L, LPPassManager &LPM) {
if (skipOptnoneFunction(L))
return false;
CurLoop = L;
// If the loop could not be converted to canonical form, it must have an
// indirectbr in it, just give up.
if (!L->getLoopPreheader())
return false;
// Disable loop idiom recognition if the function's name is a common idiom.
StringRef Name = L->getHeader()->getParent()->getName();
if (Name == "memset" || Name == "memcpy")
return false;
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-10 01:55:00 +08:00
AA = &getAnalysis<AAResultsWrapperPass>().getAAResults();
DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
[PM] Port ScalarEvolution to the new pass manager. This change makes ScalarEvolution a stand-alone object and just produces one from a pass as needed. Making this work well requires making the object movable, using references instead of overwritten pointers in a number of places, and other refactorings. I've also wired it up to the new pass manager and added a RUN line to a test to exercise it under the new pass manager. This includes basic printing support much like with other analyses. But there is a big and somewhat scary change here. Prior to this patch ScalarEvolution was never *actually* invalidated!!! Re-running the pass just re-wired up the various other analyses and didn't remove any of the existing entries in the SCEV caches or clear out anything at all. This might seem OK as everything in SCEV that can uses ValueHandles to track updates to the values that serve as SCEV keys. However, this still means that as we ran SCEV over each function in the module, we kept accumulating more and more SCEVs into the cache. At the end, we would have a SCEV cache with every value that we ever needed a SCEV for in the entire module!!! Yowzers. The releaseMemory routine would dump all of this, but that isn't realy called during normal runs of the pipeline as far as I can see. To make matters worse, there *is* actually a key that we don't update with value handles -- there is a map keyed off of Loop*s. Because LoopInfo *does* release its memory from run to run, it is entirely possible to run SCEV over one function, then over another function, and then lookup a Loop* from the second function but find an entry inserted for the first function! Ouch. To make matters still worse, there are plenty of updates that *don't* trip a value handle. It seems incredibly unlikely that today GVN or another pass that invalidates SCEV can update values in *just* such a way that a subsequent run of SCEV will incorrectly find lookups in a cache, but it is theoretically possible and would be a nightmare to debug. With this refactoring, I've fixed all this by actually destroying and recreating the ScalarEvolution object from run to run. Technically, this could increase the amount of malloc traffic we see, but then again it is also technically correct. ;] I don't actually think we're suffering from tons of malloc traffic from SCEV because if we were, the fact that we never clear the memory would seem more likely to have come up as an actual problem before now. So, I've made the simple fix here. If in fact there are serious issues with too much allocation and deallocation, I can work on a clever fix that preserves the allocations (while clearing the data) between each run, but I'd prefer to do that kind of optimization with a test case / benchmark that shows why we need such cleverness (and that can test that we actually make it faster). It's possible that this will make some things faster by making the SCEV caches have higher locality (due to being significantly smaller) so until there is a clear benchmark, I think the simple change is best. Differential Revision: http://reviews.llvm.org/D12063 llvm-svn: 245193
2015-08-17 10:08:17 +08:00
SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE();
TLI = &getAnalysis<TargetLibraryInfoWrapperPass>().getTLI();
TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(
*CurLoop->getHeader()->getParent());
if (SE->hasLoopInvariantBackedgeTakenCount(L))
return runOnCountableLoop();
return runOnNoncountableLoop();
}
bool LoopIdiomRecognize::runOnCountableLoop() {
const SCEV *BECount = SE->getBackedgeTakenCount(CurLoop);
assert(!isa<SCEVCouldNotCompute>(BECount) &&
"runOnCountableLoop() called on a loop without a predictable"
"backedge-taken count");
// If this loop executes exactly one time, then it should be peeled, not
// optimized by this pass.
if (const SCEVConstant *BECst = dyn_cast<SCEVConstant>(BECount))
if (BECst->getValue()->getValue() == 0)
return false;
SmallVector<BasicBlock *, 8> ExitBlocks;
CurLoop->getUniqueExitBlocks(ExitBlocks);
DEBUG(dbgs() << "loop-idiom Scanning: F["
<< CurLoop->getHeader()->getParent()->getName() << "] Loop %"
<< CurLoop->getHeader()->getName() << "\n");
bool MadeChange = false;
// Scan all the blocks in the loop that are not in subloops.
for (auto *BB : CurLoop->getBlocks()) {
// Ignore blocks in subloops.
if (LI->getLoopFor(BB) != CurLoop)
continue;
MadeChange |= runOnLoopBlock(BB, BECount, ExitBlocks);
}
return MadeChange;
}
/// runOnLoopBlock - Process the specified block, which lives in a counted loop
/// with the specified backedge count. This block is known to be in the current
/// loop and not in any subloops.
bool LoopIdiomRecognize::runOnLoopBlock(
BasicBlock *BB, const SCEV *BECount,
SmallVectorImpl<BasicBlock *> &ExitBlocks) {
// We can only promote stores in this block if they are unconditionally
// executed in the loop. For a block to be unconditionally executed, it has
// to dominate all the exit blocks of the loop. Verify this now.
for (unsigned i = 0, e = ExitBlocks.size(); i != e; ++i)
if (!DT->dominates(BB, ExitBlocks[i]))
return false;
bool MadeChange = false;
for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E;) {
Instruction *Inst = &*I++;
// Look for store instructions, which may be optimized to memset/memcpy.
if (StoreInst *SI = dyn_cast<StoreInst>(Inst)) {
WeakVH InstPtr(&*I);
if (!processLoopStore(SI, BECount))
continue;
MadeChange = true;
// If processing the store invalidated our iterator, start over from the
// top of the block.
if (!InstPtr)
I = BB->begin();
continue;
}
// Look for memset instructions, which may be optimized to a larger memset.
if (MemSetInst *MSI = dyn_cast<MemSetInst>(Inst)) {
WeakVH InstPtr(&*I);
if (!processLoopMemSet(MSI, BECount))
continue;
MadeChange = true;
// If processing the memset invalidated our iterator, start over from the
// top of the block.
if (!InstPtr)
I = BB->begin();
continue;
}
}
return MadeChange;
}
/// processLoopStore - See if this store can be promoted to a memset or memcpy.
bool LoopIdiomRecognize::processLoopStore(StoreInst *SI, const SCEV *BECount) {
if (!SI->isSimple())
return false;
Value *StoredVal = SI->getValueOperand();
Value *StorePtr = SI->getPointerOperand();
// Reject stores that are so large that they overflow an unsigned.
auto &DL = CurLoop->getHeader()->getModule()->getDataLayout();
uint64_t SizeInBits = DL.getTypeSizeInBits(StoredVal->getType());
if ((SizeInBits & 7) || (SizeInBits >> 32) != 0)
return false;
// See if the pointer expression is an AddRec like {base,+,1} on the current
// loop, which indicates a strided store. If we have something else, it's a
// random store we can't handle.
const SCEVAddRecExpr *StoreEv =
dyn_cast<SCEVAddRecExpr>(SE->getSCEV(StorePtr));
if (!StoreEv || StoreEv->getLoop() != CurLoop || !StoreEv->isAffine())
return false;
// Check to see if the stride matches the size of the store. If so, then we
// know that every byte is touched in the loop.
unsigned StoreSize = (unsigned)SizeInBits >> 3;
const SCEVConstant *ConstStride =
dyn_cast<SCEVConstant>(StoreEv->getOperand(1));
if (!ConstStride)
return false;
APInt Stride = ConstStride->getValue()->getValue();
if (StoreSize != Stride && StoreSize != -Stride)
return false;
bool NegStride = StoreSize == -Stride;
// See if we can optimize just this store in isolation.
if (processLoopStridedStore(StorePtr, StoreSize, SI->getAlignment(),
StoredVal, SI, StoreEv, BECount, NegStride))
return true;
// TODO: We don't handle negative stride memcpys.
if (NegStride)
return false;
// If the stored value is a strided load in the same loop with the same stride
// this this may be transformable into a memcpy. This kicks in for stuff like
// for (i) A[i] = B[i];
if (LoadInst *LI = dyn_cast<LoadInst>(StoredVal)) {
const SCEVAddRecExpr *LoadEv =
dyn_cast<SCEVAddRecExpr>(SE->getSCEV(LI->getOperand(0)));
if (LoadEv && LoadEv->getLoop() == CurLoop && LoadEv->isAffine() &&
StoreEv->getOperand(1) == LoadEv->getOperand(1) && LI->isSimple())
if (processLoopStoreOfLoopLoad(SI, StoreSize, StoreEv, LoadEv, BECount))
return true;
}
// errs() << "UNHANDLED strided store: " << *StoreEv << " - " << *SI << "\n";
return false;
}
/// processLoopMemSet - See if this memset can be promoted to a large memset.
bool LoopIdiomRecognize::processLoopMemSet(MemSetInst *MSI,
const SCEV *BECount) {
// We can only handle non-volatile memsets with a constant size.
if (MSI->isVolatile() || !isa<ConstantInt>(MSI->getLength()))
return false;
// If we're not allowed to hack on memset, we fail.
if (!TLI->has(LibFunc::memset))
return false;
Value *Pointer = MSI->getDest();
// See if the pointer expression is an AddRec like {base,+,1} on the current
// loop, which indicates a strided store. If we have something else, it's a
// random store we can't handle.
const SCEVAddRecExpr *Ev = dyn_cast<SCEVAddRecExpr>(SE->getSCEV(Pointer));
if (!Ev || Ev->getLoop() != CurLoop || !Ev->isAffine())
return false;
// Reject memsets that are so large that they overflow an unsigned.
uint64_t SizeInBytes = cast<ConstantInt>(MSI->getLength())->getZExtValue();
if ((SizeInBytes >> 32) != 0)
return false;
// Check to see if the stride matches the size of the memset. If so, then we
// know that every byte is touched in the loop.
const SCEVConstant *Stride = dyn_cast<SCEVConstant>(Ev->getOperand(1));
// TODO: Could also handle negative stride here someday, that will require the
// validity check in mayLoopAccessLocation to be updated though.
if (!Stride || MSI->getLength() != Stride->getValue())
return false;
return processLoopStridedStore(Pointer, (unsigned)SizeInBytes,
MSI->getAlignment(), MSI->getValue(), MSI, Ev,
BECount, /*NegStride=*/false);
}
/// mayLoopAccessLocation - Return true if the specified loop might access the
/// specified pointer location, which is a loop-strided access. The 'Access'
/// argument specifies what the verboten forms of access are (read or write).
static bool mayLoopAccessLocation(Value *Ptr, ModRefInfo Access, Loop *L,
const SCEV *BECount, unsigned StoreSize,
AliasAnalysis &AA,
Instruction *IgnoredStore) {
// Get the location that may be stored across the loop. Since the access is
// strided positively through memory, we say that the modified location starts
// at the pointer and has infinite size.
uint64_t AccessSize = MemoryLocation::UnknownSize;
// If the loop iterates a fixed number of times, we can refine the access size
// to be exactly the size of the memset, which is (BECount+1)*StoreSize
if (const SCEVConstant *BECst = dyn_cast<SCEVConstant>(BECount))
AccessSize = (BECst->getValue()->getZExtValue() + 1) * StoreSize;
// TODO: For this to be really effective, we have to dive into the pointer
// operand in the store. Store to &A[i] of 100 will always return may alias
// with store of &A[100], we need to StoreLoc to be "A" with size of 100,
// which will then no-alias a store to &A[100].
MemoryLocation StoreLoc(Ptr, AccessSize);
for (Loop::block_iterator BI = L->block_begin(), E = L->block_end(); BI != E;
++BI)
for (BasicBlock::iterator I = (*BI)->begin(), E = (*BI)->end(); I != E; ++I)
if (&*I != IgnoredStore && (AA.getModRefInfo(&*I, StoreLoc) & Access))
return true;
return false;
}
/// getMemSetPatternValue - If a strided store of the specified value is safe to
/// turn into a memset_pattern16, return a ConstantArray of 16 bytes that should
/// be passed in. Otherwise, return null.
///
/// Note that we don't ever attempt to use memset_pattern8 or 4, because these
/// just replicate their input array and then pass on to memset_pattern16.
static Constant *getMemSetPatternValue(Value *V, const DataLayout &DL) {
// If the value isn't a constant, we can't promote it to being in a constant
// array. We could theoretically do a store to an alloca or something, but
// that doesn't seem worthwhile.
Constant *C = dyn_cast<Constant>(V);
if (!C)
return nullptr;
// Only handle simple values that are a power of two bytes in size.
uint64_t Size = DL.getTypeSizeInBits(V->getType());
if (Size == 0 || (Size & 7) || (Size & (Size - 1)))
return nullptr;
// Don't care enough about darwin/ppc to implement this.
if (DL.isBigEndian())
return nullptr;
// Convert to size in bytes.
Size /= 8;
// TODO: If CI is larger than 16-bytes, we can try slicing it in half to see
// if the top and bottom are the same (e.g. for vectors and large integers).
if (Size > 16)
return nullptr;
// If the constant is exactly 16 bytes, just use it.
if (Size == 16)
return C;
// Otherwise, we'll use an array of the constants.
unsigned ArraySize = 16 / Size;
ArrayType *AT = ArrayType::get(V->getType(), ArraySize);
return ConstantArray::get(AT, std::vector<Constant *>(ArraySize, C));
}
/// processLoopStridedStore - We see a strided store of some value. If we can
/// transform this into a memset or memset_pattern in the loop preheader, do so.
bool LoopIdiomRecognize::processLoopStridedStore(
Value *DestPtr, unsigned StoreSize, unsigned StoreAlignment,
Value *StoredVal, Instruction *TheStore, const SCEVAddRecExpr *Ev,
const SCEV *BECount, bool NegStride) {
// If the stored value is a byte-wise value (like i32 -1), then it may be
// turned into a memset of i8 -1, assuming that all the consecutive bytes
// are stored. A store of i32 0x01020304 can never be turned into a memset,
// but it can be turned into memset_pattern if the target supports it.
Value *SplatValue = isBytewiseValue(StoredVal);
Constant *PatternValue = nullptr;
auto &DL = CurLoop->getHeader()->getModule()->getDataLayout();
unsigned DestAS = DestPtr->getType()->getPointerAddressSpace();
// If we're allowed to form a memset, and the stored value would be acceptable
// for memset, use it.
if (SplatValue && TLI->has(LibFunc::memset) &&
// Verify that the stored value is loop invariant. If not, we can't
// promote the memset.
CurLoop->isLoopInvariant(SplatValue)) {
// Keep and use SplatValue.
PatternValue = nullptr;
} else if (DestAS == 0 && TLI->has(LibFunc::memset_pattern16) &&
(PatternValue = getMemSetPatternValue(StoredVal, DL))) {
// Don't create memset_pattern16s with address spaces.
// It looks like we can use PatternValue!
SplatValue = nullptr;
} else {
// Otherwise, this isn't an idiom we can transform. For example, we can't
// do anything with a 3-byte store.
return false;
}
// The trip count of the loop and the base pointer of the addrec SCEV is
// guaranteed to be loop invariant, which means that it should dominate the
// header. This allows us to insert code for it in the preheader.
BasicBlock *Preheader = CurLoop->getLoopPreheader();
IRBuilder<> Builder(Preheader->getTerminator());
SCEVExpander Expander(*SE, DL, "loop-idiom");
Type *DestInt8PtrTy = Builder.getInt8PtrTy(DestAS);
Type *IntPtr = Builder.getIntPtrTy(DL, DestAS);
const SCEV *Start = Ev->getStart();
// If we have a negative stride, Start refers to the end of the memory
// location we're trying to memset. Therefore, we need to recompute the start
// point, which is just Start - BECount*Size.
if (NegStride) {
const SCEV *Index = SE->getTruncateOrZeroExtend(BECount, IntPtr);
if (StoreSize != 1)
Index = SE->getMulExpr(Index, SE->getConstant(IntPtr, StoreSize),
SCEV::FlagNUW);
Start = SE->getMinusSCEV(Ev->getStart(), Index);
}
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// Okay, we have a strided store "p[i]" of a splattable value. We can turn
// this into a memset in the loop preheader now if we want. However, this
// would be unsafe to do if there is anything else in the loop that may read
// or write to the aliased location. Check for any overlap by generating the
// base pointer and checking the region.
Value *BasePtr =
Expander.expandCodeFor(Start, DestInt8PtrTy, Preheader->getTerminator());
if (mayLoopAccessLocation(BasePtr, MRI_ModRef, CurLoop, BECount, StoreSize,
*AA, TheStore)) {
Expander.clear();
// If we generated new code for the base pointer, clean up.
RecursivelyDeleteTriviallyDeadInstructions(BasePtr, TLI);
return false;
}
// Okay, everything looks good, insert the memset.
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// The # stored bytes is (BECount+1)*Size. Expand the trip count out to
// pointer size if it isn't already.
BECount = SE->getTruncateOrZeroExtend(BECount, IntPtr);
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const SCEV *NumBytesS =
SE->getAddExpr(BECount, SE->getOne(IntPtr), SCEV::FlagNUW);
if (StoreSize != 1) {
NumBytesS = SE->getMulExpr(NumBytesS, SE->getConstant(IntPtr, StoreSize),
SCEV::FlagNUW);
}
Value *NumBytes =
Expander.expandCodeFor(NumBytesS, IntPtr, Preheader->getTerminator());
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CallInst *NewCall;
if (SplatValue) {
NewCall =
Builder.CreateMemSet(BasePtr, SplatValue, NumBytes, StoreAlignment);
} else {
// Everything is emitted in default address space
Type *Int8PtrTy = DestInt8PtrTy;
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Module *M = TheStore->getParent()->getParent()->getParent();
Value *MSP =
M->getOrInsertFunction("memset_pattern16", Builder.getVoidTy(),
Int8PtrTy, Int8PtrTy, IntPtr, (void *)nullptr);
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// Otherwise we should form a memset_pattern16. PatternValue is known to be
// an constant array of 16-bytes. Plop the value into a mergable global.
GlobalVariable *GV = new GlobalVariable(*M, PatternValue->getType(), true,
GlobalValue::PrivateLinkage,
PatternValue, ".memset_pattern");
GV->setUnnamedAddr(true); // Ok to merge these.
GV->setAlignment(16);
Value *PatternPtr = ConstantExpr::getBitCast(GV, Int8PtrTy);
NewCall = Builder.CreateCall(MSP, {BasePtr, PatternPtr, NumBytes});
}
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DEBUG(dbgs() << " Formed memset: " << *NewCall << "\n"
<< " from store to: " << *Ev << " at: " << *TheStore << "\n");
NewCall->setDebugLoc(TheStore->getDebugLoc());
// Okay, the memset has been formed. Zap the original store and anything that
// feeds into it.
deleteDeadInstruction(TheStore, TLI);
++NumMemSet;
return true;
}
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/// processLoopStoreOfLoopLoad - We see a strided store whose value is a
/// same-strided load.
bool LoopIdiomRecognize::processLoopStoreOfLoopLoad(
StoreInst *SI, unsigned StoreSize, const SCEVAddRecExpr *StoreEv,
const SCEVAddRecExpr *LoadEv, const SCEV *BECount) {
// If we're not allowed to form memcpy, we fail.
if (!TLI->has(LibFunc::memcpy))
return false;
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LoadInst *LI = cast<LoadInst>(SI->getValueOperand());
// The trip count of the loop and the base pointer of the addrec SCEV is
// guaranteed to be loop invariant, which means that it should dominate the
// header. This allows us to insert code for it in the preheader.
BasicBlock *Preheader = CurLoop->getLoopPreheader();
IRBuilder<> Builder(Preheader->getTerminator());
const DataLayout &DL = Preheader->getModule()->getDataLayout();
SCEVExpander Expander(*SE, DL, "loop-idiom");
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// Okay, we have a strided store "p[i]" of a loaded value. We can turn
// this into a memcpy in the loop preheader now if we want. However, this
// would be unsafe to do if there is anything else in the loop that may read
// or write the memory region we're storing to. This includes the load that
// feeds the stores. Check for an alias by generating the base address and
// checking everything.
Value *StoreBasePtr = Expander.expandCodeFor(
StoreEv->getStart(), Builder.getInt8PtrTy(SI->getPointerAddressSpace()),
Preheader->getTerminator());
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if (mayLoopAccessLocation(StoreBasePtr, MRI_ModRef, CurLoop, BECount,
StoreSize, *AA, SI)) {
Expander.clear();
// If we generated new code for the base pointer, clean up.
RecursivelyDeleteTriviallyDeadInstructions(StoreBasePtr, TLI);
return false;
}
// For a memcpy, we have to make sure that the input array is not being
// mutated by the loop.
Value *LoadBasePtr = Expander.expandCodeFor(
LoadEv->getStart(), Builder.getInt8PtrTy(LI->getPointerAddressSpace()),
Preheader->getTerminator());
if (mayLoopAccessLocation(LoadBasePtr, MRI_Mod, CurLoop, BECount, StoreSize,
*AA, SI)) {
Expander.clear();
// If we generated new code for the base pointer, clean up.
RecursivelyDeleteTriviallyDeadInstructions(LoadBasePtr, TLI);
RecursivelyDeleteTriviallyDeadInstructions(StoreBasePtr, TLI);
return false;
}
// Okay, everything is safe, we can transform this!
// The # stored bytes is (BECount+1)*Size. Expand the trip count out to
// pointer size if it isn't already.
Type *IntPtrTy = Builder.getIntPtrTy(DL, SI->getPointerAddressSpace());
BECount = SE->getTruncateOrZeroExtend(BECount, IntPtrTy);
const SCEV *NumBytesS =
SE->getAddExpr(BECount, SE->getOne(IntPtrTy), SCEV::FlagNUW);
if (StoreSize != 1)
NumBytesS = SE->getMulExpr(NumBytesS, SE->getConstant(IntPtrTy, StoreSize),
SCEV::FlagNUW);
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Value *NumBytes =
Expander.expandCodeFor(NumBytesS, IntPtrTy, Preheader->getTerminator());
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CallInst *NewCall =
Builder.CreateMemCpy(StoreBasePtr, LoadBasePtr, NumBytes,
std::min(SI->getAlignment(), LI->getAlignment()));
NewCall->setDebugLoc(SI->getDebugLoc());
DEBUG(dbgs() << " Formed memcpy: " << *NewCall << "\n"
<< " from load ptr=" << *LoadEv << " at: " << *LI << "\n"
<< " from store ptr=" << *StoreEv << " at: " << *SI << "\n");
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// Okay, the memcpy has been formed. Zap the original store and anything that
// feeds into it.
deleteDeadInstruction(SI, TLI);
++NumMemCpy;
return true;
}
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bool LoopIdiomRecognize::runOnNoncountableLoop() {
if (recognizePopcount())
return true;
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return false;
}
/// Check if the given conditional branch is based on the comparison between
/// a variable and zero, and if the variable is non-zero, the control yields to
/// the loop entry. If the branch matches the behavior, the variable involved
/// in the comparion is returned. This function will be called to see if the
/// precondition and postcondition of the loop are in desirable form.
static Value *matchCondition(BranchInst *BI, BasicBlock *LoopEntry) {
if (!BI || !BI->isConditional())
return nullptr;
ICmpInst *Cond = dyn_cast<ICmpInst>(BI->getCondition());
if (!Cond)
return nullptr;
ConstantInt *CmpZero = dyn_cast<ConstantInt>(Cond->getOperand(1));
if (!CmpZero || !CmpZero->isZero())
return nullptr;
ICmpInst::Predicate Pred = Cond->getPredicate();
if ((Pred == ICmpInst::ICMP_NE && BI->getSuccessor(0) == LoopEntry) ||
(Pred == ICmpInst::ICMP_EQ && BI->getSuccessor(1) == LoopEntry))
return Cond->getOperand(0);
return nullptr;
}
/// Return true iff the idiom is detected in the loop.
///
/// Additionally:
/// 1) \p CntInst is set to the instruction counting the population bit.
/// 2) \p CntPhi is set to the corresponding phi node.
/// 3) \p Var is set to the value whose population bits are being counted.
///
/// The core idiom we are trying to detect is:
/// \code
/// if (x0 != 0)
/// goto loop-exit // the precondition of the loop
/// cnt0 = init-val;
/// do {
/// x1 = phi (x0, x2);
/// cnt1 = phi(cnt0, cnt2);
///
/// cnt2 = cnt1 + 1;
/// ...
/// x2 = x1 & (x1 - 1);
/// ...
/// } while(x != 0);
///
/// loop-exit:
/// \endcode
static bool detectPopcountIdiom(Loop *CurLoop, BasicBlock *PreCondBB,
Instruction *&CntInst, PHINode *&CntPhi,
Value *&Var) {
// step 1: Check to see if the look-back branch match this pattern:
// "if (a!=0) goto loop-entry".
BasicBlock *LoopEntry;
Instruction *DefX2, *CountInst;
Value *VarX1, *VarX0;
PHINode *PhiX, *CountPhi;
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DefX2 = CountInst = nullptr;
VarX1 = VarX0 = nullptr;
PhiX = CountPhi = nullptr;
LoopEntry = *(CurLoop->block_begin());
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// step 1: Check if the loop-back branch is in desirable form.
{
if (Value *T = matchCondition(
dyn_cast<BranchInst>(LoopEntry->getTerminator()), LoopEntry))
DefX2 = dyn_cast<Instruction>(T);
else
return false;
}
// step 2: detect instructions corresponding to "x2 = x1 & (x1 - 1)"
{
if (!DefX2 || DefX2->getOpcode() != Instruction::And)
return false;
BinaryOperator *SubOneOp;
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if ((SubOneOp = dyn_cast<BinaryOperator>(DefX2->getOperand(0))))
VarX1 = DefX2->getOperand(1);
else {
VarX1 = DefX2->getOperand(0);
SubOneOp = dyn_cast<BinaryOperator>(DefX2->getOperand(1));
}
if (!SubOneOp)
return false;
Instruction *SubInst = cast<Instruction>(SubOneOp);
ConstantInt *Dec = dyn_cast<ConstantInt>(SubInst->getOperand(1));
if (!Dec ||
!((SubInst->getOpcode() == Instruction::Sub && Dec->isOne()) ||
(SubInst->getOpcode() == Instruction::Add &&
Dec->isAllOnesValue()))) {
return false;
}
}
// step 3: Check the recurrence of variable X
{
PhiX = dyn_cast<PHINode>(VarX1);
if (!PhiX ||
(PhiX->getOperand(0) != DefX2 && PhiX->getOperand(1) != DefX2)) {
return false;
}
}
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// step 4: Find the instruction which count the population: cnt2 = cnt1 + 1
{
CountInst = nullptr;
for (BasicBlock::iterator Iter = LoopEntry->getFirstNonPHI()->getIterator(),
IterE = LoopEntry->end();
Iter != IterE; Iter++) {
Instruction *Inst = &*Iter;
if (Inst->getOpcode() != Instruction::Add)
continue;
ConstantInt *Inc = dyn_cast<ConstantInt>(Inst->getOperand(1));
if (!Inc || !Inc->isOne())
continue;
PHINode *Phi = dyn_cast<PHINode>(Inst->getOperand(0));
if (!Phi || Phi->getParent() != LoopEntry)
continue;
// Check if the result of the instruction is live of the loop.
bool LiveOutLoop = false;
for (User *U : Inst->users()) {
if ((cast<Instruction>(U))->getParent() != LoopEntry) {
LiveOutLoop = true;
break;
}
}
if (LiveOutLoop) {
CountInst = Inst;
CountPhi = Phi;
break;
}
}
if (!CountInst)
return false;
}
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// step 5: check if the precondition is in this form:
// "if (x != 0) goto loop-head ; else goto somewhere-we-don't-care;"
{
auto *PreCondBr = dyn_cast<BranchInst>(PreCondBB->getTerminator());
Value *T = matchCondition(PreCondBr, CurLoop->getLoopPreheader());
if (T != PhiX->getOperand(0) && T != PhiX->getOperand(1))
return false;
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CntInst = CountInst;
CntPhi = CountPhi;
Var = T;
}
return true;
}
/// Recognizes a population count idiom in a non-countable loop.
///
/// If detected, transforms the relevant code to issue the popcount intrinsic
/// function call, and returns true; otherwise, returns false.
bool LoopIdiomRecognize::recognizePopcount() {
if (TTI->getPopcntSupport(32) != TargetTransformInfo::PSK_FastHardware)
return false;
// Counting population are usually conducted by few arithmetic instructions.
// Such instructions can be easily "absorbed" by vacant slots in a
// non-compact loop. Therefore, recognizing popcount idiom only makes sense
// in a compact loop.
// Give up if the loop has multiple blocks or multiple backedges.
if (CurLoop->getNumBackEdges() != 1 || CurLoop->getNumBlocks() != 1)
return false;
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BasicBlock *LoopBody = *(CurLoop->block_begin());
if (LoopBody->size() >= 20) {
// The loop is too big, bail out.
return false;
}
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// It should have a preheader containing nothing but an unconditional branch.
BasicBlock *PH = CurLoop->getLoopPreheader();
if (!PH)
return false;
if (&PH->front() != PH->getTerminator())
return false;
auto *EntryBI = dyn_cast<BranchInst>(PH->getTerminator());
if (!EntryBI || EntryBI->isConditional())
return false;
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// It should have a precondition block where the generated popcount instrinsic
// function can be inserted.
auto *PreCondBB = PH->getSinglePredecessor();
if (!PreCondBB)
return false;
auto *PreCondBI = dyn_cast<BranchInst>(PreCondBB->getTerminator());
if (!PreCondBI || PreCondBI->isUnconditional())
return false;
Instruction *CntInst;
PHINode *CntPhi;
Value *Val;
if (!detectPopcountIdiom(CurLoop, PreCondBB, CntInst, CntPhi, Val))
return false;
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transformLoopToPopcount(PreCondBB, CntInst, CntPhi, Val);
return true;
}
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static CallInst *createPopcntIntrinsic(IRBuilder<> &IRBuilder, Value *Val,
DebugLoc DL) {
Value *Ops[] = {Val};
Type *Tys[] = {Val->getType()};
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Module *M = IRBuilder.GetInsertBlock()->getParent()->getParent();
Value *Func = Intrinsic::getDeclaration(M, Intrinsic::ctpop, Tys);
CallInst *CI = IRBuilder.CreateCall(Func, Ops);
CI->setDebugLoc(DL);
return CI;
}
void LoopIdiomRecognize::transformLoopToPopcount(BasicBlock *PreCondBB,
Instruction *CntInst,
PHINode *CntPhi, Value *Var) {
BasicBlock *PreHead = CurLoop->getLoopPreheader();
auto *PreCondBr = dyn_cast<BranchInst>(PreCondBB->getTerminator());
const DebugLoc DL = CntInst->getDebugLoc();
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// Assuming before transformation, the loop is following:
// if (x) // the precondition
// do { cnt++; x &= x - 1; } while(x);
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// Step 1: Insert the ctpop instruction at the end of the precondition block
IRBuilder<> Builder(PreCondBr);
Value *PopCnt, *PopCntZext, *NewCount, *TripCnt;
{
PopCnt = createPopcntIntrinsic(Builder, Var, DL);
NewCount = PopCntZext =
Builder.CreateZExtOrTrunc(PopCnt, cast<IntegerType>(CntPhi->getType()));
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if (NewCount != PopCnt)
(cast<Instruction>(NewCount))->setDebugLoc(DL);
// TripCnt is exactly the number of iterations the loop has
TripCnt = NewCount;
// If the population counter's initial value is not zero, insert Add Inst.
Value *CntInitVal = CntPhi->getIncomingValueForBlock(PreHead);
ConstantInt *InitConst = dyn_cast<ConstantInt>(CntInitVal);
if (!InitConst || !InitConst->isZero()) {
NewCount = Builder.CreateAdd(NewCount, CntInitVal);
(cast<Instruction>(NewCount))->setDebugLoc(DL);
}
}
// Step 2: Replace the precondition from "if (x == 0) goto loop-exit" to
// "if (NewCount == 0) loop-exit". Without this change, the intrinsic
// function would be partial dead code, and downstream passes will drag
// it back from the precondition block to the preheader.
{
ICmpInst *PreCond = cast<ICmpInst>(PreCondBr->getCondition());
Value *Opnd0 = PopCntZext;
Value *Opnd1 = ConstantInt::get(PopCntZext->getType(), 0);
if (PreCond->getOperand(0) != Var)
std::swap(Opnd0, Opnd1);
ICmpInst *NewPreCond = cast<ICmpInst>(
Builder.CreateICmp(PreCond->getPredicate(), Opnd0, Opnd1));
PreCondBr->setCondition(NewPreCond);
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RecursivelyDeleteTriviallyDeadInstructions(PreCond, TLI);
}
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// Step 3: Note that the population count is exactly the trip count of the
// loop in question, which enable us to to convert the loop from noncountable
// loop into a countable one. The benefit is twofold:
//
// - If the loop only counts population, the entire loop becomes dead after
// the transformation. It is a lot easier to prove a countable loop dead
// than to prove a noncountable one. (In some C dialects, an infinite loop
// isn't dead even if it computes nothing useful. In general, DCE needs
// to prove a noncountable loop finite before safely delete it.)
//
// - If the loop also performs something else, it remains alive.
// Since it is transformed to countable form, it can be aggressively
// optimized by some optimizations which are in general not applicable
// to a noncountable loop.
//
// After this step, this loop (conceptually) would look like following:
// newcnt = __builtin_ctpop(x);
// t = newcnt;
// if (x)
// do { cnt++; x &= x-1; t--) } while (t > 0);
BasicBlock *Body = *(CurLoop->block_begin());
{
auto *LbBr = dyn_cast<BranchInst>(Body->getTerminator());
ICmpInst *LbCond = cast<ICmpInst>(LbBr->getCondition());
Type *Ty = TripCnt->getType();
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PHINode *TcPhi = PHINode::Create(Ty, 2, "tcphi", &Body->front());
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Builder.SetInsertPoint(LbCond);
Instruction *TcDec = cast<Instruction>(
Builder.CreateSub(TcPhi, ConstantInt::get(Ty, 1),
"tcdec", false, true));
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TcPhi->addIncoming(TripCnt, PreHead);
TcPhi->addIncoming(TcDec, Body);
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CmpInst::Predicate Pred =
(LbBr->getSuccessor(0) == Body) ? CmpInst::ICMP_UGT : CmpInst::ICMP_SLE;
LbCond->setPredicate(Pred);
LbCond->setOperand(0, TcDec);
LbCond->setOperand(1, ConstantInt::get(Ty, 0));
}
// Step 4: All the references to the original population counter outside
// the loop are replaced with the NewCount -- the value returned from
// __builtin_ctpop().
CntInst->replaceUsesOutsideBlock(NewCount, Body);
// step 5: Forget the "non-computable" trip-count SCEV associated with the
// loop. The loop would otherwise not be deleted even if it becomes empty.
SE->forgetLoop(CurLoop);
}