2015-05-27 18:44:32 +00:00
|
|
|
//===- DivergenceAnalysis.cpp ------ Divergence Analysis ------------------===//
|
|
|
|
//
|
|
|
|
// The LLVM Compiler Infrastructure
|
|
|
|
//
|
|
|
|
// This file is distributed under the University of Illinois Open Source
|
|
|
|
// License. See LICENSE.TXT for details.
|
|
|
|
//
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
//
|
|
|
|
// This file defines divergence analysis which determines whether a branch in a
|
|
|
|
// GPU program is divergent. It can help branch optimizations such as jump
|
|
|
|
// threading and loop unswitching to make better decisions.
|
|
|
|
//
|
|
|
|
// GPU programs typically use the SIMD execution model, where multiple threads
|
|
|
|
// in the same execution group have to execute in lock-step. Therefore, if the
|
|
|
|
// code contains divergent branches (i.e., threads in a group do not agree on
|
|
|
|
// which path of the branch to take), the group of threads has to execute all
|
|
|
|
// the paths from that branch with different subsets of threads enabled until
|
|
|
|
// they converge at the immediately post-dominating BB of the paths.
|
|
|
|
//
|
|
|
|
// Due to this execution model, some optimizations such as jump
|
|
|
|
// threading and loop unswitching can be unfortunately harmful when performed on
|
|
|
|
// divergent branches. Therefore, an analysis that computes which branches in a
|
|
|
|
// GPU program are divergent can help the compiler to selectively run these
|
|
|
|
// optimizations.
|
|
|
|
//
|
|
|
|
// This file defines divergence analysis which computes a conservative but
|
|
|
|
// non-trivial approximation of all divergent branches in a GPU program. It
|
|
|
|
// partially implements the approach described in
|
|
|
|
//
|
|
|
|
// Divergence Analysis
|
|
|
|
// Sampaio, Souza, Collange, Pereira
|
|
|
|
// TOPLAS '13
|
|
|
|
//
|
|
|
|
// The divergence analysis identifies the sources of divergence (e.g., special
|
|
|
|
// variables that hold the thread ID), and recursively marks variables that are
|
|
|
|
// data or sync dependent on a source of divergence as divergent.
|
|
|
|
//
|
|
|
|
// While data dependency is a well-known concept, the notion of sync dependency
|
|
|
|
// is worth more explanation. Sync dependence characterizes the control flow
|
|
|
|
// aspect of the propagation of branch divergence. For example,
|
|
|
|
//
|
|
|
|
// %cond = icmp slt i32 %tid, 10
|
|
|
|
// br i1 %cond, label %then, label %else
|
|
|
|
// then:
|
|
|
|
// br label %merge
|
|
|
|
// else:
|
|
|
|
// br label %merge
|
|
|
|
// merge:
|
|
|
|
// %a = phi i32 [ 0, %then ], [ 1, %else ]
|
|
|
|
//
|
|
|
|
// Suppose %tid holds the thread ID. Although %a is not data dependent on %tid
|
|
|
|
// because %tid is not on its use-def chains, %a is sync dependent on %tid
|
|
|
|
// because the branch "br i1 %cond" depends on %tid and affects which value %a
|
|
|
|
// is assigned to.
|
|
|
|
//
|
|
|
|
// The current implementation has the following limitations:
|
|
|
|
// 1. intra-procedural. It conservatively considers the arguments of a
|
|
|
|
// non-kernel-entry function and the return value of a function call as
|
|
|
|
// divergent.
|
|
|
|
// 2. memory as black box. It conservatively considers values loaded from
|
|
|
|
// generic or local address as divergent. This can be improved by leveraging
|
|
|
|
// pointer analysis.
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
|
|
|
|
#include <vector>
|
|
|
|
#include "llvm/IR/Dominators.h"
|
|
|
|
#include "llvm/ADT/DenseSet.h"
|
|
|
|
#include "llvm/Analysis/Passes.h"
|
|
|
|
#include "llvm/Analysis/PostDominators.h"
|
|
|
|
#include "llvm/Analysis/TargetTransformInfo.h"
|
|
|
|
#include "llvm/IR/Function.h"
|
|
|
|
#include "llvm/IR/InstIterator.h"
|
|
|
|
#include "llvm/IR/Instructions.h"
|
|
|
|
#include "llvm/IR/IntrinsicInst.h"
|
|
|
|
#include "llvm/IR/Value.h"
|
|
|
|
#include "llvm/Pass.h"
|
|
|
|
#include "llvm/Support/CommandLine.h"
|
|
|
|
#include "llvm/Support/Debug.h"
|
|
|
|
#include "llvm/Support/raw_ostream.h"
|
|
|
|
#include "llvm/Transforms/Scalar.h"
|
|
|
|
using namespace llvm;
|
|
|
|
|
|
|
|
#define DEBUG_TYPE "divergence"
|
|
|
|
|
|
|
|
namespace {
|
|
|
|
class DivergenceAnalysis : public FunctionPass {
|
|
|
|
public:
|
|
|
|
static char ID;
|
|
|
|
|
|
|
|
DivergenceAnalysis() : FunctionPass(ID) {
|
|
|
|
initializeDivergenceAnalysisPass(*PassRegistry::getPassRegistry());
|
|
|
|
}
|
|
|
|
|
|
|
|
void getAnalysisUsage(AnalysisUsage &AU) const override {
|
|
|
|
AU.addRequired<DominatorTreeWrapperPass>();
|
|
|
|
AU.addRequired<PostDominatorTree>();
|
|
|
|
AU.setPreservesAll();
|
|
|
|
}
|
|
|
|
|
|
|
|
bool runOnFunction(Function &F) override;
|
|
|
|
|
|
|
|
// Print all divergent branches in the function.
|
|
|
|
void print(raw_ostream &OS, const Module *) const override;
|
|
|
|
|
|
|
|
// Returns true if V is divergent.
|
|
|
|
bool isDivergent(const Value *V) const { return DivergentValues.count(V); }
|
|
|
|
// Returns true if V is uniform/non-divergent.
|
|
|
|
bool isUniform(const Value *V) const { return !isDivergent(V); }
|
|
|
|
|
|
|
|
private:
|
|
|
|
// Stores all divergent values.
|
|
|
|
DenseSet<const Value *> DivergentValues;
|
|
|
|
};
|
|
|
|
} // End of anonymous namespace
|
|
|
|
|
|
|
|
// Register this pass.
|
|
|
|
char DivergenceAnalysis::ID = 0;
|
|
|
|
INITIALIZE_PASS_BEGIN(DivergenceAnalysis, "divergence", "Divergence Analysis",
|
|
|
|
false, true)
|
|
|
|
INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
|
|
|
|
INITIALIZE_PASS_DEPENDENCY(PostDominatorTree)
|
|
|
|
INITIALIZE_PASS_END(DivergenceAnalysis, "divergence", "Divergence Analysis",
|
|
|
|
false, true)
|
|
|
|
|
|
|
|
namespace {
|
|
|
|
|
|
|
|
class DivergencePropagator {
|
|
|
|
public:
|
|
|
|
DivergencePropagator(Function &F, TargetTransformInfo &TTI,
|
|
|
|
DominatorTree &DT, PostDominatorTree &PDT,
|
|
|
|
DenseSet<const Value *> &DV)
|
|
|
|
: F(F), TTI(TTI), DT(DT), PDT(PDT), DV(DV) {}
|
|
|
|
void populateWithSourcesOfDivergence();
|
|
|
|
void propagate();
|
|
|
|
|
|
|
|
private:
|
|
|
|
// A helper function that explores data dependents of V.
|
|
|
|
void exploreDataDependency(Value *V);
|
|
|
|
// A helper function that explores sync dependents of TI.
|
|
|
|
void exploreSyncDependency(TerminatorInst *TI);
|
|
|
|
// Computes the influence region from Start to End. This region includes all
|
|
|
|
// basic blocks on any path from Start to End.
|
|
|
|
void computeInfluenceRegion(BasicBlock *Start, BasicBlock *End,
|
|
|
|
DenseSet<BasicBlock *> &InfluenceRegion);
|
|
|
|
// Finds all users of I that are outside the influence region, and add these
|
|
|
|
// users to Worklist.
|
|
|
|
void findUsersOutsideInfluenceRegion(
|
|
|
|
Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion);
|
|
|
|
|
|
|
|
Function &F;
|
|
|
|
TargetTransformInfo &TTI;
|
|
|
|
DominatorTree &DT;
|
|
|
|
PostDominatorTree &PDT;
|
|
|
|
std::vector<Value *> Worklist; // Stack for DFS.
|
|
|
|
DenseSet<const Value *> &DV; // Stores all divergent values.
|
|
|
|
};
|
|
|
|
|
|
|
|
void DivergencePropagator::populateWithSourcesOfDivergence() {
|
|
|
|
Worklist.clear();
|
|
|
|
DV.clear();
|
|
|
|
for (auto &I : inst_range(F)) {
|
|
|
|
if (TTI.isSourceOfDivergence(&I)) {
|
|
|
|
Worklist.push_back(&I);
|
|
|
|
DV.insert(&I);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
for (auto &Arg : F.args()) {
|
|
|
|
if (TTI.isSourceOfDivergence(&Arg)) {
|
|
|
|
Worklist.push_back(&Arg);
|
|
|
|
DV.insert(&Arg);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void DivergencePropagator::exploreSyncDependency(TerminatorInst *TI) {
|
|
|
|
// Propagation rule 1: if branch TI is divergent, all PHINodes in TI's
|
|
|
|
// immediate post dominator are divergent. This rule handles if-then-else
|
|
|
|
// patterns. For example,
|
|
|
|
//
|
|
|
|
// if (tid < 5)
|
|
|
|
// a1 = 1;
|
|
|
|
// else
|
|
|
|
// a2 = 2;
|
|
|
|
// a = phi(a1, a2); // sync dependent on (tid < 5)
|
|
|
|
BasicBlock *ThisBB = TI->getParent();
|
|
|
|
BasicBlock *IPostDom = PDT.getNode(ThisBB)->getIDom()->getBlock();
|
|
|
|
if (IPostDom == nullptr)
|
|
|
|
return;
|
|
|
|
|
|
|
|
for (auto I = IPostDom->begin(); isa<PHINode>(I); ++I) {
|
|
|
|
// A PHINode is uniform if it returns the same value no matter which path is
|
|
|
|
// taken.
|
|
|
|
if (!cast<PHINode>(I)->hasConstantValue() && DV.insert(I).second)
|
|
|
|
Worklist.push_back(I);
|
|
|
|
}
|
|
|
|
|
|
|
|
// Propagation rule 2: if a value defined in a loop is used outside, the user
|
|
|
|
// is sync dependent on the condition of the loop exits that dominate the
|
|
|
|
// user. For example,
|
|
|
|
//
|
|
|
|
// int i = 0;
|
|
|
|
// do {
|
|
|
|
// i++;
|
|
|
|
// if (foo(i)) ... // uniform
|
|
|
|
// } while (i < tid);
|
|
|
|
// if (bar(i)) ... // divergent
|
|
|
|
//
|
|
|
|
// A program may contain unstructured loops. Therefore, we cannot leverage
|
|
|
|
// LoopInfo, which only recognizes natural loops.
|
|
|
|
//
|
|
|
|
// The algorithm used here handles both natural and unstructured loops. Given
|
|
|
|
// a branch TI, we first compute its influence region, the union of all simple
|
|
|
|
// paths from TI to its immediate post dominator (IPostDom). Then, we search
|
|
|
|
// for all the values defined in the influence region but used outside. All
|
|
|
|
// these users are sync dependent on TI.
|
|
|
|
DenseSet<BasicBlock *> InfluenceRegion;
|
|
|
|
computeInfluenceRegion(ThisBB, IPostDom, InfluenceRegion);
|
|
|
|
// An insight that can speed up the search process is that all the in-region
|
|
|
|
// values that are used outside must dominate TI. Therefore, instead of
|
|
|
|
// searching every basic blocks in the influence region, we search all the
|
|
|
|
// dominators of TI until it is outside the influence region.
|
|
|
|
BasicBlock *InfluencedBB = ThisBB;
|
|
|
|
while (InfluenceRegion.count(InfluencedBB)) {
|
|
|
|
for (auto &I : *InfluencedBB)
|
|
|
|
findUsersOutsideInfluenceRegion(I, InfluenceRegion);
|
|
|
|
DomTreeNode *IDomNode = DT.getNode(InfluencedBB)->getIDom();
|
|
|
|
if (IDomNode == nullptr)
|
|
|
|
break;
|
|
|
|
InfluencedBB = IDomNode->getBlock();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void DivergencePropagator::findUsersOutsideInfluenceRegion(
|
|
|
|
Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion) {
|
|
|
|
for (User *U : I.users()) {
|
|
|
|
Instruction *UserInst = cast<Instruction>(U);
|
|
|
|
if (!InfluenceRegion.count(UserInst->getParent())) {
|
|
|
|
if (DV.insert(UserInst).second)
|
|
|
|
Worklist.push_back(UserInst);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void DivergencePropagator::computeInfluenceRegion(
|
|
|
|
BasicBlock *Start, BasicBlock *End,
|
|
|
|
DenseSet<BasicBlock *> &InfluenceRegion) {
|
|
|
|
assert(PDT.properlyDominates(End, Start) &&
|
|
|
|
"End does not properly dominate Start");
|
|
|
|
std::vector<BasicBlock *> InfluenceStack;
|
|
|
|
InfluenceStack.push_back(Start);
|
|
|
|
InfluenceRegion.insert(Start);
|
|
|
|
while (!InfluenceStack.empty()) {
|
|
|
|
BasicBlock *BB = InfluenceStack.back();
|
|
|
|
InfluenceStack.pop_back();
|
|
|
|
for (BasicBlock *Succ : successors(BB)) {
|
|
|
|
if (End != Succ && InfluenceRegion.insert(Succ).second)
|
|
|
|
InfluenceStack.push_back(Succ);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void DivergencePropagator::exploreDataDependency(Value *V) {
|
|
|
|
// Follow def-use chains of V.
|
|
|
|
for (User *U : V->users()) {
|
|
|
|
Instruction *UserInst = cast<Instruction>(U);
|
|
|
|
if (DV.insert(UserInst).second)
|
|
|
|
Worklist.push_back(UserInst);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void DivergencePropagator::propagate() {
|
|
|
|
// Traverse the dependency graph using DFS.
|
|
|
|
while (!Worklist.empty()) {
|
|
|
|
Value *V = Worklist.back();
|
|
|
|
Worklist.pop_back();
|
|
|
|
if (TerminatorInst *TI = dyn_cast<TerminatorInst>(V)) {
|
|
|
|
// Terminators with less than two successors won't introduce sync
|
|
|
|
// dependency. Ignore them.
|
|
|
|
if (TI->getNumSuccessors() > 1)
|
|
|
|
exploreSyncDependency(TI);
|
|
|
|
}
|
|
|
|
exploreDataDependency(V);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2015-07-05 14:21:36 +00:00
|
|
|
} /// end namespace anonymous
|
2015-05-27 18:44:32 +00:00
|
|
|
|
|
|
|
FunctionPass *llvm::createDivergenceAnalysisPass() {
|
|
|
|
return new DivergenceAnalysis();
|
|
|
|
}
|
|
|
|
|
|
|
|
bool DivergenceAnalysis::runOnFunction(Function &F) {
|
|
|
|
auto *TTIWP = getAnalysisIfAvailable<TargetTransformInfoWrapperPass>();
|
|
|
|
if (TTIWP == nullptr)
|
|
|
|
return false;
|
|
|
|
|
|
|
|
TargetTransformInfo &TTI = TTIWP->getTTI(F);
|
|
|
|
// Fast path: if the target does not have branch divergence, we do not mark
|
|
|
|
// any branch as divergent.
|
|
|
|
if (!TTI.hasBranchDivergence())
|
|
|
|
return false;
|
|
|
|
|
|
|
|
DivergentValues.clear();
|
|
|
|
DivergencePropagator DP(F, TTI,
|
|
|
|
getAnalysis<DominatorTreeWrapperPass>().getDomTree(),
|
|
|
|
getAnalysis<PostDominatorTree>(), DivergentValues);
|
|
|
|
DP.populateWithSourcesOfDivergence();
|
|
|
|
DP.propagate();
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
void DivergenceAnalysis::print(raw_ostream &OS, const Module *) const {
|
|
|
|
if (DivergentValues.empty())
|
|
|
|
return;
|
|
|
|
const Value *FirstDivergentValue = *DivergentValues.begin();
|
|
|
|
const Function *F;
|
|
|
|
if (const Argument *Arg = dyn_cast<Argument>(FirstDivergentValue)) {
|
|
|
|
F = Arg->getParent();
|
|
|
|
} else if (const Instruction *I =
|
|
|
|
dyn_cast<Instruction>(FirstDivergentValue)) {
|
|
|
|
F = I->getParent()->getParent();
|
|
|
|
} else {
|
|
|
|
llvm_unreachable("Only arguments and instructions can be divergent");
|
|
|
|
}
|
|
|
|
|
|
|
|
// Dumps all divergent values in F, arguments and then instructions.
|
|
|
|
for (auto &Arg : F->args()) {
|
|
|
|
if (DivergentValues.count(&Arg))
|
|
|
|
OS << "DIVERGENT: " << Arg << "\n";
|
|
|
|
}
|
|
|
|
// Iterate instructions using inst_range to ensure a deterministic order.
|
|
|
|
for (auto &I : inst_range(F)) {
|
|
|
|
if (DivergentValues.count(&I))
|
|
|
|
OS << "DIVERGENT:" << I << "\n";
|
|
|
|
}
|
|
|
|
}
|