llvm-6502/lib/Transforms/Scalar/LoopDistribute.cpp

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New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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//===- LoopDistribute.cpp - Loop Distribution Pass ------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This file implements the Loop Distribution Pass. Its main focus is to
// distribute loops that cannot be vectorized due to dependence cycles. It
// tries to isolate the offending dependences into a new loop allowing
// vectorization of the remaining parts.
//
// For dependence analysis, the pass uses the LoopVectorizer's
// LoopAccessAnalysis. Because this analysis presumes no change in the order of
// memory operations, special care is taken to preserve the lexical order of
// these operations.
//
// Similarly to the Vectorizer, the pass also supports loop versioning to
// run-time disambiguate potentially overlapping arrays.
//
//===----------------------------------------------------------------------===//
#include "llvm/ADT/DepthFirstIterator.h"
#include "llvm/ADT/EquivalenceClasses.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/Statistic.h"
#include "llvm/Analysis/LoopAccessAnalysis.h"
#include "llvm/Analysis/LoopInfo.h"
#include "llvm/IR/Dominators.h"
#include "llvm/Pass.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#include "llvm/Transforms/Utils/BasicBlockUtils.h"
#include "llvm/Transforms/Utils/Cloning.h"
#include "llvm/Transforms/Utils/LoopVersioning.h"
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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#include <list>
#define LDIST_NAME "loop-distribute"
#define DEBUG_TYPE LDIST_NAME
using namespace llvm;
static cl::opt<bool>
LDistVerify("loop-distribute-verify", cl::Hidden,
cl::desc("Turn on DominatorTree and LoopInfo verification "
"after Loop Distribution"),
cl::init(false));
static cl::opt<bool> DistributeNonIfConvertible(
"loop-distribute-non-if-convertible", cl::Hidden,
cl::desc("Whether to distribute into a loop that may not be "
"if-convertible by the loop vectorizer"),
cl::init(false));
STATISTIC(NumLoopsDistributed, "Number of loops distributed");
namespace {
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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/// \brief Maintains the set of instructions of the loop for a partition before
/// cloning. After cloning, it hosts the new loop.
class InstPartition {
typedef SmallPtrSet<Instruction *, 8> InstructionSet;
public:
InstPartition(Instruction *I, Loop *L, bool DepCycle = false)
: DepCycle(DepCycle), OrigLoop(L), ClonedLoop(nullptr) {
Set.insert(I);
}
/// \brief Returns whether this partition contains a dependence cycle.
bool hasDepCycle() const { return DepCycle; }
/// \brief Adds an instruction to this partition.
void add(Instruction *I) { Set.insert(I); }
/// \brief Collection accessors.
InstructionSet::iterator begin() { return Set.begin(); }
InstructionSet::iterator end() { return Set.end(); }
InstructionSet::const_iterator begin() const { return Set.begin(); }
InstructionSet::const_iterator end() const { return Set.end(); }
bool empty() const { return Set.empty(); }
/// \brief Moves this partition into \p Other. This partition becomes empty
/// after this.
void moveTo(InstPartition &Other) {
Other.Set.insert(Set.begin(), Set.end());
Set.clear();
Other.DepCycle |= DepCycle;
}
/// \brief Populates the partition with a transitive closure of all the
/// instructions that the seeded instructions dependent on.
void populateUsedSet() {
// FIXME: We currently don't use control-dependence but simply include all
// blocks (possibly empty at the end) and let simplifycfg mostly clean this
// up.
for (auto *B : OrigLoop->getBlocks())
Set.insert(B->getTerminator());
// Follow the use-def chains to form a transitive closure of all the
// instructions that the originally seeded instructions depend on.
SmallVector<Instruction *, 8> Worklist(Set.begin(), Set.end());
while (!Worklist.empty()) {
Instruction *I = Worklist.pop_back_val();
// Insert instructions from the loop that we depend on.
for (Value *V : I->operand_values()) {
auto *I = dyn_cast<Instruction>(V);
if (I && OrigLoop->contains(I->getParent()) && Set.insert(I).second)
Worklist.push_back(I);
}
}
}
/// \brief Clones the original loop.
///
/// Updates LoopInfo and DominatorTree using the information that block \p
/// LoopDomBB dominates the loop.
Loop *cloneLoopWithPreheader(BasicBlock *InsertBefore, BasicBlock *LoopDomBB,
unsigned Index, LoopInfo *LI,
DominatorTree *DT) {
ClonedLoop = ::cloneLoopWithPreheader(InsertBefore, LoopDomBB, OrigLoop,
VMap, Twine(".ldist") + Twine(Index),
LI, DT, ClonedLoopBlocks);
return ClonedLoop;
}
/// \brief The cloned loop. If this partition is mapped to the original loop,
/// this is null.
const Loop *getClonedLoop() const { return ClonedLoop; }
/// \brief Returns the loop where this partition ends up after distribution.
/// If this partition is mapped to the original loop then use the block from
/// the loop.
const Loop *getDistributedLoop() const {
return ClonedLoop ? ClonedLoop : OrigLoop;
}
/// \brief The VMap that is populated by cloning and then used in
/// remapinstruction to remap the cloned instructions.
ValueToValueMapTy &getVMap() { return VMap; }
/// \brief Remaps the cloned instructions using VMap.
void remapInstructions() {
remapInstructionsInBlocks(ClonedLoopBlocks, VMap);
}
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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/// \brief Based on the set of instructions selected for this partition,
/// removes the unnecessary ones.
void removeUnusedInsts() {
SmallVector<Instruction *, 8> Unused;
for (auto *Block : OrigLoop->getBlocks())
for (auto &Inst : *Block)
if (!Set.count(&Inst)) {
Instruction *NewInst = &Inst;
if (!VMap.empty())
NewInst = cast<Instruction>(VMap[NewInst]);
assert(!isa<BranchInst>(NewInst) &&
"Branches are marked used early on");
Unused.push_back(NewInst);
}
// Delete the instructions backwards, as it has a reduced likelihood of
// having to update as many def-use and use-def chains.
for (auto *Inst : make_range(Unused.rbegin(), Unused.rend())) {
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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if (!Inst->use_empty())
Inst->replaceAllUsesWith(UndefValue::get(Inst->getType()));
Inst->eraseFromParent();
}
}
void print() const {
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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if (DepCycle)
dbgs() << " (cycle)\n";
for (auto *I : Set)
// Prefix with the block name.
dbgs() << " " << I->getParent()->getName() << ":" << *I << "\n";
}
void printBlocks() const {
for (auto *BB : getDistributedLoop()->getBlocks())
dbgs() << *BB;
}
private:
/// \brief Instructions from OrigLoop selected for this partition.
InstructionSet Set;
/// \brief Whether this partition contains a dependence cycle.
bool DepCycle;
/// \brief The original loop.
Loop *OrigLoop;
/// \brief The cloned loop. If this partition is mapped to the original loop,
/// this is null.
Loop *ClonedLoop;
/// \brief The blocks of ClonedLoop including the preheader. If this
/// partition is mapped to the original loop, this is empty.
SmallVector<BasicBlock *, 8> ClonedLoopBlocks;
/// \brief These gets populated once the set of instructions have been
/// finalized. If this partition is mapped to the original loop, these are not
/// set.
ValueToValueMapTy VMap;
};
/// \brief Holds the set of Partitions. It populates them, merges them and then
/// clones the loops.
class InstPartitionContainer {
typedef DenseMap<Instruction *, int> InstToPartitionIdT;
public:
InstPartitionContainer(Loop *L, LoopInfo *LI, DominatorTree *DT)
: L(L), LI(LI), DT(DT) {}
/// \brief Returns the number of partitions.
unsigned getSize() const { return PartitionContainer.size(); }
/// \brief Adds \p Inst into the current partition if that is marked to
/// contain cycles. Otherwise start a new partition for it.
void addToCyclicPartition(Instruction *Inst) {
// If the current partition is non-cyclic. Start a new one.
if (PartitionContainer.empty() || !PartitionContainer.back().hasDepCycle())
PartitionContainer.emplace_back(Inst, L, /*DepCycle=*/true);
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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else
PartitionContainer.back().add(Inst);
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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}
/// \brief Adds \p Inst into a partition that is not marked to contain
/// dependence cycles.
///
// Initially we isolate memory instructions into as many partitions as
// possible, then later we may merge them back together.
void addToNewNonCyclicPartition(Instruction *Inst) {
PartitionContainer.emplace_back(Inst, L);
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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}
/// \brief Merges adjacent non-cyclic partitions.
///
/// The idea is that we currently only want to isolate the non-vectorizable
/// partition. We could later allow more distribution among these partition
/// too.
void mergeAdjacentNonCyclic() {
mergeAdjacentPartitionsIf(
[](const InstPartition *P) { return !P->hasDepCycle(); });
}
/// \brief If a partition contains only conditional stores, we won't vectorize
/// it. Try to merge it with a previous cyclic partition.
void mergeNonIfConvertible() {
mergeAdjacentPartitionsIf([&](const InstPartition *Partition) {
if (Partition->hasDepCycle())
return true;
// Now, check if all stores are conditional in this partition.
bool seenStore = false;
for (auto *Inst : *Partition)
if (isa<StoreInst>(Inst)) {
seenStore = true;
if (!LoopAccessInfo::blockNeedsPredication(Inst->getParent(), L, DT))
return false;
}
return seenStore;
});
}
/// \brief Merges the partitions according to various heuristics.
void mergeBeforePopulating() {
mergeAdjacentNonCyclic();
if (!DistributeNonIfConvertible)
mergeNonIfConvertible();
}
/// \brief Merges partitions in order to ensure that no loads are duplicated.
///
/// We can't duplicate loads because that could potentially reorder them.
/// LoopAccessAnalysis provides dependency information with the context that
/// the order of memory operation is preserved.
///
/// Return if any partitions were merged.
bool mergeToAvoidDuplicatedLoads() {
typedef DenseMap<Instruction *, InstPartition *> LoadToPartitionT;
typedef EquivalenceClasses<InstPartition *> ToBeMergedT;
LoadToPartitionT LoadToPartition;
ToBeMergedT ToBeMerged;
// Step through the partitions and create equivalence between partitions
// that contain the same load. Also put partitions in between them in the
// same equivalence class to avoid reordering of memory operations.
for (PartitionContainerT::iterator I = PartitionContainer.begin(),
E = PartitionContainer.end();
I != E; ++I) {
auto *PartI = &*I;
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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// If a load occurs in two partitions PartI and PartJ, merge all
// partitions (PartI, PartJ] into PartI.
for (Instruction *Inst : *PartI)
if (isa<LoadInst>(Inst)) {
bool NewElt;
LoadToPartitionT::iterator LoadToPart;
std::tie(LoadToPart, NewElt) =
LoadToPartition.insert(std::make_pair(Inst, PartI));
if (!NewElt) {
DEBUG(dbgs() << "Merging partitions due to this load in multiple "
<< "partitions: " << PartI << ", "
<< LoadToPart->second << "\n" << *Inst << "\n");
auto PartJ = I;
do {
--PartJ;
ToBeMerged.unionSets(PartI, &*PartJ);
} while (&*PartJ != LoadToPart->second);
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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}
}
}
if (ToBeMerged.empty())
return false;
// Merge the member of an equivalence class into its class leader. This
// makes the members empty.
for (ToBeMergedT::iterator I = ToBeMerged.begin(), E = ToBeMerged.end();
I != E; ++I) {
if (!I->isLeader())
continue;
auto PartI = I->getData();
for (auto PartJ : make_range(std::next(ToBeMerged.member_begin(I)),
ToBeMerged.member_end())) {
PartJ->moveTo(*PartI);
}
}
// Remove the empty partitions.
PartitionContainer.remove_if(
[](const InstPartition &P) { return P.empty(); });
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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return true;
}
/// \brief Sets up the mapping between instructions to partitions. If the
/// instruction is duplicated across multiple partitions, set the entry to -1.
void setupPartitionIdOnInstructions() {
int PartitionID = 0;
for (const auto &Partition : PartitionContainer) {
for (Instruction *Inst : Partition) {
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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bool NewElt;
InstToPartitionIdT::iterator Iter;
std::tie(Iter, NewElt) =
InstToPartitionId.insert(std::make_pair(Inst, PartitionID));
if (!NewElt)
Iter->second = -1;
}
++PartitionID;
}
}
/// \brief Populates the partition with everything that the seeding
/// instructions require.
void populateUsedSet() {
for (auto &P : PartitionContainer)
P.populateUsedSet();
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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}
/// \brief This performs the main chunk of the work of cloning the loops for
/// the partitions.
void cloneLoops(Pass *P) {
BasicBlock *OrigPH = L->getLoopPreheader();
// At this point the predecessor of the preheader is either the memcheck
// block or the top part of the original preheader.
BasicBlock *Pred = OrigPH->getSinglePredecessor();
assert(Pred && "Preheader does not have a single predecessor");
BasicBlock *ExitBlock = L->getExitBlock();
assert(ExitBlock && "No single exit block");
Loop *NewLoop;
assert(!PartitionContainer.empty() && "at least two partitions expected");
// We're cloning the preheader along with the loop so we already made sure
// it was empty.
assert(&*OrigPH->begin() == OrigPH->getTerminator() &&
"preheader not empty");
// Create a loop for each partition except the last. Clone the original
// loop before PH along with adding a preheader for the cloned loop. Then
// update PH to point to the newly added preheader.
BasicBlock *TopPH = OrigPH;
unsigned Index = getSize() - 1;
for (auto I = std::next(PartitionContainer.rbegin()),
E = PartitionContainer.rend();
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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I != E; ++I, --Index, TopPH = NewLoop->getLoopPreheader()) {
auto *Part = &*I;
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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NewLoop = Part->cloneLoopWithPreheader(TopPH, Pred, Index, LI, DT);
Part->getVMap()[ExitBlock] = TopPH;
Part->remapInstructions();
}
Pred->getTerminator()->replaceUsesOfWith(OrigPH, TopPH);
// Now go in forward order and update the immediate dominator for the
// preheaders with the exiting block of the previous loop. Dominance
// within the loop is updated in cloneLoopWithPreheader.
for (auto Curr = PartitionContainer.cbegin(),
Next = std::next(PartitionContainer.cbegin()),
E = PartitionContainer.cend();
Next != E; ++Curr, ++Next)
DT->changeImmediateDominator(
Next->getDistributedLoop()->getLoopPreheader(),
Curr->getDistributedLoop()->getExitingBlock());
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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}
/// \brief Removes the dead instructions from the cloned loops.
void removeUnusedInsts() {
for (auto &Partition : PartitionContainer)
Partition.removeUnusedInsts();
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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}
/// \brief For each memory pointer, it computes the partitionId the pointer is
/// used in.
///
/// This returns an array of int where the I-th entry corresponds to I-th
/// entry in LAI.getRuntimePointerCheck(). If the pointer is used in multiple
/// partitions its entry is set to -1.
SmallVector<int, 8>
computePartitionSetForPointers(const LoopAccessInfo &LAI) {
const RuntimePointerChecking *RtPtrCheck = LAI.getRuntimePointerChecking();
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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unsigned N = RtPtrCheck->Pointers.size();
SmallVector<int, 8> PtrToPartitions(N);
for (unsigned I = 0; I < N; ++I) {
Value *Ptr = RtPtrCheck->Pointers[I].PointerValue;
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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auto Instructions =
LAI.getInstructionsForAccess(Ptr, RtPtrCheck->Pointers[I].IsWritePtr);
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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int &Partition = PtrToPartitions[I];
// First set it to uninitialized.
Partition = -2;
for (Instruction *Inst : Instructions) {
// Note that this could be -1 if Inst is duplicated across multiple
// partitions.
int ThisPartition = this->InstToPartitionId[Inst];
if (Partition == -2)
Partition = ThisPartition;
// -1 means belonging to multiple partitions.
else if (Partition == -1)
break;
else if (Partition != (int)ThisPartition)
Partition = -1;
}
assert(Partition != -2 && "Pointer not belonging to any partition");
}
return PtrToPartitions;
}
void print(raw_ostream &OS) const {
unsigned Index = 0;
for (const auto &P : PartitionContainer) {
OS << "Partition " << Index++ << " (" << &P << "):\n";
P.print();
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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}
}
void dump() const { print(dbgs()); }
#ifndef NDEBUG
friend raw_ostream &operator<<(raw_ostream &OS,
const InstPartitionContainer &Partitions) {
Partitions.print(OS);
return OS;
}
#endif
void printBlocks() const {
unsigned Index = 0;
for (const auto &P : PartitionContainer) {
dbgs() << "\nPartition " << Index++ << " (" << &P << "):\n";
P.printBlocks();
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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}
}
private:
typedef std::list<InstPartition> PartitionContainerT;
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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/// \brief List of partitions.
PartitionContainerT PartitionContainer;
/// \brief Mapping from Instruction to partition Id. If the instruction
/// belongs to multiple partitions the entry contains -1.
InstToPartitionIdT InstToPartitionId;
Loop *L;
LoopInfo *LI;
DominatorTree *DT;
/// \brief The control structure to merge adjacent partitions if both satisfy
/// the \p Predicate.
template <class UnaryPredicate>
void mergeAdjacentPartitionsIf(UnaryPredicate Predicate) {
InstPartition *PrevMatch = nullptr;
for (auto I = PartitionContainer.begin(); I != PartitionContainer.end();) {
auto DoesMatch = Predicate(&*I);
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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if (PrevMatch == nullptr && DoesMatch) {
PrevMatch = &*I;
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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++I;
} else if (PrevMatch != nullptr && DoesMatch) {
I->moveTo(*PrevMatch);
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
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I = PartitionContainer.erase(I);
} else {
PrevMatch = nullptr;
++I;
}
}
}
};
/// \brief For each memory instruction, this class maintains difference of the
/// number of unsafe dependences that start out from this instruction minus
/// those that end here.
///
/// By traversing the memory instructions in program order and accumulating this
/// number, we know whether any unsafe dependence crosses over a program point.
class MemoryInstructionDependences {
typedef MemoryDepChecker::Dependence Dependence;
public:
struct Entry {
Instruction *Inst;
unsigned NumUnsafeDependencesStartOrEnd;
Entry(Instruction *Inst) : Inst(Inst), NumUnsafeDependencesStartOrEnd(0) {}
};
typedef SmallVector<Entry, 8> AccessesType;
AccessesType::const_iterator begin() const { return Accesses.begin(); }
AccessesType::const_iterator end() const { return Accesses.end(); }
MemoryInstructionDependences(
const SmallVectorImpl<Instruction *> &Instructions,
const SmallVectorImpl<Dependence> &InterestingDependences) {
Accesses.append(Instructions.begin(), Instructions.end());
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
2015-05-14 12:05:18 +00:00
DEBUG(dbgs() << "Backward dependences:\n");
for (auto &Dep : InterestingDependences)
if (Dep.isPossiblyBackward()) {
// Note that the designations source and destination follow the program
// order, i.e. source is always first. (The direction is given by the
// DepType.)
++Accesses[Dep.Source].NumUnsafeDependencesStartOrEnd;
--Accesses[Dep.Destination].NumUnsafeDependencesStartOrEnd;
DEBUG(Dep.print(dbgs(), 2, Instructions));
}
}
private:
AccessesType Accesses;
};
/// \brief Returns the instructions that use values defined in the loop.
static SmallVector<Instruction *, 8> findDefsUsedOutsideOfLoop(Loop *L) {
SmallVector<Instruction *, 8> UsedOutside;
for (auto *Block : L->getBlocks())
// FIXME: I believe that this could use copy_if if the Inst reference could
// be adapted into a pointer.
for (auto &Inst : *Block) {
auto Users = Inst.users();
if (std::any_of(Users.begin(), Users.end(), [&](User *U) {
auto *Use = cast<Instruction>(U);
return !L->contains(Use->getParent());
}))
UsedOutside.push_back(&Inst);
}
return UsedOutside;
}
/// \brief The pass class.
class LoopDistribute : public FunctionPass {
public:
LoopDistribute() : FunctionPass(ID) {
initializeLoopDistributePass(*PassRegistry::getPassRegistry());
}
bool runOnFunction(Function &F) override {
LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
LAA = &getAnalysis<LoopAccessAnalysis>();
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)
Changed |= processLoop(L);
// Process each loop nest in the function.
return Changed;
}
void getAnalysisUsage(AnalysisUsage &AU) const override {
AU.addRequired<LoopInfoWrapperPass>();
AU.addPreserved<LoopInfoWrapperPass>();
AU.addRequired<LoopAccessAnalysis>();
AU.addRequired<DominatorTreeWrapperPass>();
AU.addPreserved<DominatorTreeWrapperPass>();
}
static char ID;
private:
/// \brief Filter out checks between pointers from the same partition.
///
/// \p PtrToPartition contains the partition number for pointers. Partition
/// number -1 means that the pointer is used in multiple partitions. In this
/// case we can't safely omit the check.
SmallVector<RuntimePointerChecking::PointerCheck, 4>
includeOnlyCrossPartitionChecks(
const SmallVectorImpl<RuntimePointerChecking::PointerCheck> &AllChecks,
const SmallVectorImpl<int> &PtrToPartition,
const RuntimePointerChecking *RtPtrChecking) {
SmallVector<RuntimePointerChecking::PointerCheck, 4> Checks;
std::copy_if(AllChecks.begin(), AllChecks.end(), std::back_inserter(Checks),
[&](const RuntimePointerChecking::PointerCheck &Check) {
for (unsigned PtrIdx1 : Check.first->Members)
for (unsigned PtrIdx2 : Check.second->Members)
// Only include this check if there is a pair of pointers
// that require checking and the pointers fall into
// separate partitions.
//
// (Note that we already know at this point that the two
// pointer groups need checking but it doesn't follow
// that each pair of pointers within the two groups need
// checking as well.
//
// In other words we don't want to include a check just
// because there is a pair of pointers between the two
// pointer groups that require checks and a different
// pair whose pointers fall into different partitions.)
if (RtPtrChecking->needsChecking(PtrIdx1, PtrIdx2) &&
!RuntimePointerChecking::arePointersInSamePartition(
PtrToPartition, PtrIdx1, PtrIdx2))
return true;
return false;
});
return Checks;
}
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
2015-05-14 12:05:18 +00:00
/// \brief Try to distribute an inner-most loop.
bool processLoop(Loop *L) {
assert(L->empty() && "Only process inner loops.");
DEBUG(dbgs() << "\nLDist: In \"" << L->getHeader()->getParent()->getName()
<< "\" checking " << *L << "\n");
BasicBlock *PH = L->getLoopPreheader();
if (!PH) {
DEBUG(dbgs() << "Skipping; no preheader");
return false;
}
if (!L->getExitBlock()) {
DEBUG(dbgs() << "Skipping; multiple exit blocks");
return false;
}
// LAA will check that we only have a single exiting block.
const LoopAccessInfo &LAI = LAA->getInfo(L, ValueToValueMap());
// Currently, we only distribute to isolate the part of the loop with
// dependence cycles to enable partial vectorization.
if (LAI.canVectorizeMemory()) {
DEBUG(dbgs() << "Skipping; memory operations are safe for vectorization");
return false;
}
auto *InterestingDependences =
LAI.getDepChecker().getInterestingDependences();
if (!InterestingDependences || InterestingDependences->empty()) {
DEBUG(dbgs() << "Skipping; No unsafe dependences to isolate");
return false;
}
InstPartitionContainer Partitions(L, LI, DT);
// First, go through each memory operation and assign them to consecutive
// partitions (the order of partitions follows program order). Put those
// with unsafe dependences into "cyclic" partition otherwise put each store
// in its own "non-cyclic" partition (we'll merge these later).
//
// Note that a memory operation (e.g. Load2 below) at a program point that
// has an unsafe dependence (Store3->Load1) spanning over it must be
// included in the same cyclic partition as the dependent operations. This
// is to preserve the original program order after distribution. E.g.:
//
// NumUnsafeDependencesStartOrEnd NumUnsafeDependencesActive
// Load1 -. 1 0->1
// Load2 | /Unsafe/ 0 1
// Store3 -' -1 1->0
// Load4 0 0
//
// NumUnsafeDependencesActive > 0 indicates this situation and in this case
// we just keep assigning to the same cyclic partition until
// NumUnsafeDependencesActive reaches 0.
const MemoryDepChecker &DepChecker = LAI.getDepChecker();
MemoryInstructionDependences MID(DepChecker.getMemoryInstructions(),
*InterestingDependences);
int NumUnsafeDependencesActive = 0;
for (auto &InstDep : MID) {
Instruction *I = InstDep.Inst;
// We update NumUnsafeDependencesActive post-instruction, catch the
// start of a dependence directly via NumUnsafeDependencesStartOrEnd.
if (NumUnsafeDependencesActive ||
InstDep.NumUnsafeDependencesStartOrEnd > 0)
Partitions.addToCyclicPartition(I);
else
Partitions.addToNewNonCyclicPartition(I);
NumUnsafeDependencesActive += InstDep.NumUnsafeDependencesStartOrEnd;
assert(NumUnsafeDependencesActive >= 0 &&
"Negative number of dependences active");
}
// Add partitions for values used outside. These partitions can be out of
// order from the original program order. This is OK because if the
// partition uses a load we will merge this partition with the original
// partition of the load that we set up in the previous loop (see
// mergeToAvoidDuplicatedLoads).
auto DefsUsedOutside = findDefsUsedOutsideOfLoop(L);
for (auto *Inst : DefsUsedOutside)
Partitions.addToNewNonCyclicPartition(Inst);
DEBUG(dbgs() << "Seeded partitions:\n" << Partitions);
if (Partitions.getSize() < 2)
return false;
// Run the merge heuristics: Merge non-cyclic adjacent partitions since we
// should be able to vectorize these together.
Partitions.mergeBeforePopulating();
DEBUG(dbgs() << "\nMerged partitions:\n" << Partitions);
if (Partitions.getSize() < 2)
return false;
// Now, populate the partitions with non-memory operations.
Partitions.populateUsedSet();
DEBUG(dbgs() << "\nPopulated partitions:\n" << Partitions);
// In order to preserve original lexical order for loads, keep them in the
// partition that we set up in the MemoryInstructionDependences loop.
if (Partitions.mergeToAvoidDuplicatedLoads()) {
DEBUG(dbgs() << "\nPartitions merged to ensure unique loads:\n"
<< Partitions);
if (Partitions.getSize() < 2)
return false;
}
DEBUG(dbgs() << "\nDistributing loop: " << *L << "\n");
// We're done forming the partitions set up the reverse mapping from
// instructions to partitions.
Partitions.setupPartitionIdOnInstructions();
// To keep things simple have an empty preheader before we version or clone
// the loop. (Also split if this has no predecessor, i.e. entry, because we
// rely on PH having a predecessor.)
if (!PH->getSinglePredecessor() || &*PH->begin() != PH->getTerminator())
SplitBlock(PH, PH->getTerminator(), DT, LI);
// If we need run-time checks to disambiguate pointers are run-time, version
// the loop now.
auto PtrToPartition = Partitions.computePartitionSetForPointers(LAI);
const auto *RtPtrChecking = LAI.getRuntimePointerChecking();
auto AllChecks = RtPtrChecking->generateChecks();
auto Checks = includeOnlyCrossPartitionChecks(AllChecks, PtrToPartition,
RtPtrChecking);
if (!Checks.empty()) {
DEBUG(dbgs() << "\nPointers:\n");
DEBUG(LAI.getRuntimePointerChecking()->printChecks(dbgs(), Checks));
LoopVersioning LVer(std::move(Checks), LAI, L, LI, DT);
LVer.versionLoop(this);
LVer.addPHINodes(DefsUsedOutside);
New Loop Distribution pass Summary: This implements the initial version as was proposed earlier this year (http://lists.cs.uiuc.edu/pipermail/llvmdev/2015-January/080462.html). Since then Loop Access Analysis was split out from the Loop Vectorizer and was made into a separate analysis pass. Loop Distribution becomes the second user of this analysis. The pass is off by default and can be enabled with -enable-loop-distribution. There is currently no notion of profitability; if there is a loop with dependence cycles, the pass will try to split them off from other memory operations into a separate loop. I decided to remove the control-dependence calculation from this first version. This and the issues with the PDT are actively discussed so it probably makes sense to treat it separately. Right now I just mark all terminator instruction required which keeps identical CFGs for each distributed loop. This seems to be working pretty well for 456.hmmer where even though there is an empty if-then block in the distributed loop initially, it gets completely removed. The pass keeps DominatorTree and LoopInfo updated. I've tested this with -loop-distribute-verify with the testsuite where we distribute ~90 loops. SimplifyLoop is violated in some cases and I have a FIXME covering this. Reviewers: hfinkel, nadav, aschwaighofer Reviewed By: aschwaighofer Subscribers: llvm-commits Differential Revision: http://reviews.llvm.org/D8831 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@237358 91177308-0d34-0410-b5e6-96231b3b80d8
2015-05-14 12:05:18 +00:00
}
// Create identical copies of the original loop for each partition and hook
// them up sequentially.
Partitions.cloneLoops(this);
// Now, we remove the instruction from each loop that don't belong to that
// partition.
Partitions.removeUnusedInsts();
DEBUG(dbgs() << "\nAfter removing unused Instrs:\n");
DEBUG(Partitions.printBlocks());
if (LDistVerify) {
LI->verify();
DT->verifyDomTree();
}
++NumLoopsDistributed;
return true;
}
// Analyses used.
LoopInfo *LI;
LoopAccessAnalysis *LAA;
DominatorTree *DT;
};
} // anonymous namespace
char LoopDistribute::ID;
static const char ldist_name[] = "Loop Distribition";
INITIALIZE_PASS_BEGIN(LoopDistribute, LDIST_NAME, ldist_name, false, false)
INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(LoopAccessAnalysis)
INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
INITIALIZE_PASS_END(LoopDistribute, LDIST_NAME, ldist_name, false, false)
namespace llvm {
FunctionPass *createLoopDistributePass() { return new LoopDistribute(); }
}