409 lines
15 KiB
C++
409 lines
15 KiB
C++
//===- LegacyDivergenceAnalysis.cpp --------- Legacy Divergence Analysis
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//Implementation -==//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// This file implements divergence analysis which determines whether a branch
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// in a GPU program is divergent.It can help branch optimizations such as jump
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// threading and loop unswitching to make better decisions.
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//
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// GPU programs typically use the SIMD execution model, where multiple threads
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// in the same execution group have to execute in lock-step. Therefore, if the
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// code contains divergent branches (i.e., threads in a group do not agree on
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// which path of the branch to take), the group of threads has to execute all
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// the paths from that branch with different subsets of threads enabled until
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// they converge at the immediately post-dominating BB of the paths.
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//
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// Due to this execution model, some optimizations such as jump
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// threading and loop unswitching can be unfortunately harmful when performed on
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// divergent branches. Therefore, an analysis that computes which branches in a
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// GPU program are divergent can help the compiler to selectively run these
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// optimizations.
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//
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// This file defines divergence analysis which computes a conservative but
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// non-trivial approximation of all divergent branches in a GPU program. It
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// partially implements the approach described in
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//
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// Divergence Analysis
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// Sampaio, Souza, Collange, Pereira
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// TOPLAS '13
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//
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// The divergence analysis identifies the sources of divergence (e.g., special
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// variables that hold the thread ID), and recursively marks variables that are
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// data or sync dependent on a source of divergence as divergent.
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//
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// While data dependency is a well-known concept, the notion of sync dependency
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// is worth more explanation. Sync dependence characterizes the control flow
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// aspect of the propagation of branch divergence. For example,
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//
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// %cond = icmp slt i32 %tid, 10
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// br i1 %cond, label %then, label %else
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// then:
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// br label %merge
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// else:
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// br label %merge
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// merge:
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// %a = phi i32 [ 0, %then ], [ 1, %else ]
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//
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// Suppose %tid holds the thread ID. Although %a is not data dependent on %tid
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// because %tid is not on its use-def chains, %a is sync dependent on %tid
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// because the branch "br i1 %cond" depends on %tid and affects which value %a
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// is assigned to.
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//
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// The current implementation has the following limitations:
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// 1. intra-procedural. It conservatively considers the arguments of a
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// non-kernel-entry function and the return value of a function call as
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// divergent.
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// 2. memory as black box. It conservatively considers values loaded from
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// generic or local address as divergent. This can be improved by leveraging
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// pointer analysis.
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//
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//===----------------------------------------------------------------------===//
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#include "llvm/Analysis/LegacyDivergenceAnalysis.h"
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#include "llvm/ADT/PostOrderIterator.h"
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#include "llvm/Analysis/CFG.h"
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#include "llvm/Analysis/DivergenceAnalysis.h"
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#include "llvm/Analysis/Passes.h"
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#include "llvm/Analysis/PostDominators.h"
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#include "llvm/Analysis/TargetTransformInfo.h"
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#include "llvm/IR/Dominators.h"
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#include "llvm/IR/InstIterator.h"
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#include "llvm/IR/Instructions.h"
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#include "llvm/IR/Value.h"
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#include "llvm/InitializePasses.h"
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#include "llvm/Support/CommandLine.h"
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#include "llvm/Support/Debug.h"
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#include "llvm/Support/raw_ostream.h"
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#include <vector>
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using namespace llvm;
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#define DEBUG_TYPE "divergence"
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// transparently use the GPUDivergenceAnalysis
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static cl::opt<bool> UseGPUDA("use-gpu-divergence-analysis", cl::init(false),
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cl::Hidden,
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cl::desc("turn the LegacyDivergenceAnalysis into "
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"a wrapper for GPUDivergenceAnalysis"));
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namespace {
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class DivergencePropagator {
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public:
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DivergencePropagator(Function &F, TargetTransformInfo &TTI, DominatorTree &DT,
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PostDominatorTree &PDT, DenseSet<const Value *> &DV,
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DenseSet<const Use *> &DU)
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: F(F), TTI(TTI), DT(DT), PDT(PDT), DV(DV), DU(DU) {}
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void populateWithSourcesOfDivergence();
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void propagate();
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private:
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// A helper function that explores data dependents of V.
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void exploreDataDependency(Value *V);
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// A helper function that explores sync dependents of TI.
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void exploreSyncDependency(Instruction *TI);
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// Computes the influence region from Start to End. This region includes all
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// basic blocks on any simple path from Start to End.
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void computeInfluenceRegion(BasicBlock *Start, BasicBlock *End,
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DenseSet<BasicBlock *> &InfluenceRegion);
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// Finds all users of I that are outside the influence region, and add these
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// users to Worklist.
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void findUsersOutsideInfluenceRegion(
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Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion);
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Function &F;
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TargetTransformInfo &TTI;
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DominatorTree &DT;
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PostDominatorTree &PDT;
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std::vector<Value *> Worklist; // Stack for DFS.
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DenseSet<const Value *> &DV; // Stores all divergent values.
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DenseSet<const Use *> &DU; // Stores divergent uses of possibly uniform
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// values.
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};
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void DivergencePropagator::populateWithSourcesOfDivergence() {
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Worklist.clear();
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DV.clear();
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DU.clear();
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for (auto &I : instructions(F)) {
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if (TTI.isSourceOfDivergence(&I)) {
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Worklist.push_back(&I);
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DV.insert(&I);
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}
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}
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for (auto &Arg : F.args()) {
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if (TTI.isSourceOfDivergence(&Arg)) {
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Worklist.push_back(&Arg);
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DV.insert(&Arg);
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}
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}
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}
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void DivergencePropagator::exploreSyncDependency(Instruction *TI) {
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// Propagation rule 1: if branch TI is divergent, all PHINodes in TI's
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// immediate post dominator are divergent. This rule handles if-then-else
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// patterns. For example,
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//
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// if (tid < 5)
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// a1 = 1;
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// else
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// a2 = 2;
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// a = phi(a1, a2); // sync dependent on (tid < 5)
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BasicBlock *ThisBB = TI->getParent();
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// Unreachable blocks may not be in the dominator tree.
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if (!DT.isReachableFromEntry(ThisBB))
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return;
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// If the function has no exit blocks or doesn't reach any exit blocks, the
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// post dominator may be null.
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DomTreeNode *ThisNode = PDT.getNode(ThisBB);
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if (!ThisNode)
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return;
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BasicBlock *IPostDom = ThisNode->getIDom()->getBlock();
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if (IPostDom == nullptr)
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return;
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for (auto I = IPostDom->begin(); isa<PHINode>(I); ++I) {
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// A PHINode is uniform if it returns the same value no matter which path is
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// taken.
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if (!cast<PHINode>(I)->hasConstantOrUndefValue() && DV.insert(&*I).second)
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Worklist.push_back(&*I);
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}
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// Propagation rule 2: if a value defined in a loop is used outside, the user
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// is sync dependent on the condition of the loop exits that dominate the
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// user. For example,
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//
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// int i = 0;
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// do {
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// i++;
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// if (foo(i)) ... // uniform
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// } while (i < tid);
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// if (bar(i)) ... // divergent
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//
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// A program may contain unstructured loops. Therefore, we cannot leverage
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// LoopInfo, which only recognizes natural loops.
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//
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// The algorithm used here handles both natural and unstructured loops. Given
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// a branch TI, we first compute its influence region, the union of all simple
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// paths from TI to its immediate post dominator (IPostDom). Then, we search
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// for all the values defined in the influence region but used outside. All
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// these users are sync dependent on TI.
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DenseSet<BasicBlock *> InfluenceRegion;
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computeInfluenceRegion(ThisBB, IPostDom, InfluenceRegion);
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// An insight that can speed up the search process is that all the in-region
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// values that are used outside must dominate TI. Therefore, instead of
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// searching every basic blocks in the influence region, we search all the
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// dominators of TI until it is outside the influence region.
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BasicBlock *InfluencedBB = ThisBB;
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while (InfluenceRegion.count(InfluencedBB)) {
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for (auto &I : *InfluencedBB) {
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if (!DV.count(&I))
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findUsersOutsideInfluenceRegion(I, InfluenceRegion);
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}
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DomTreeNode *IDomNode = DT.getNode(InfluencedBB)->getIDom();
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if (IDomNode == nullptr)
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break;
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InfluencedBB = IDomNode->getBlock();
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}
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}
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void DivergencePropagator::findUsersOutsideInfluenceRegion(
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Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion) {
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for (Use &Use : I.uses()) {
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Instruction *UserInst = cast<Instruction>(Use.getUser());
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if (!InfluenceRegion.count(UserInst->getParent())) {
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DU.insert(&Use);
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if (DV.insert(UserInst).second)
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Worklist.push_back(UserInst);
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}
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}
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}
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// A helper function for computeInfluenceRegion that adds successors of "ThisBB"
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// to the influence region.
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static void
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addSuccessorsToInfluenceRegion(BasicBlock *ThisBB, BasicBlock *End,
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DenseSet<BasicBlock *> &InfluenceRegion,
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std::vector<BasicBlock *> &InfluenceStack) {
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for (BasicBlock *Succ : successors(ThisBB)) {
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if (Succ != End && InfluenceRegion.insert(Succ).second)
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InfluenceStack.push_back(Succ);
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}
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}
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void DivergencePropagator::computeInfluenceRegion(
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BasicBlock *Start, BasicBlock *End,
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DenseSet<BasicBlock *> &InfluenceRegion) {
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assert(PDT.properlyDominates(End, Start) &&
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"End does not properly dominate Start");
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// The influence region starts from the end of "Start" to the beginning of
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// "End". Therefore, "Start" should not be in the region unless "Start" is in
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// a loop that doesn't contain "End".
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std::vector<BasicBlock *> InfluenceStack;
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addSuccessorsToInfluenceRegion(Start, End, InfluenceRegion, InfluenceStack);
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while (!InfluenceStack.empty()) {
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BasicBlock *BB = InfluenceStack.back();
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InfluenceStack.pop_back();
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addSuccessorsToInfluenceRegion(BB, End, InfluenceRegion, InfluenceStack);
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}
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}
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void DivergencePropagator::exploreDataDependency(Value *V) {
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// Follow def-use chains of V.
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for (User *U : V->users()) {
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if (!TTI.isAlwaysUniform(U) && DV.insert(U).second)
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Worklist.push_back(U);
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}
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}
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void DivergencePropagator::propagate() {
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// Traverse the dependency graph using DFS.
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while (!Worklist.empty()) {
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Value *V = Worklist.back();
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Worklist.pop_back();
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if (Instruction *I = dyn_cast<Instruction>(V)) {
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// Terminators with less than two successors won't introduce sync
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// dependency. Ignore them.
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if (I->isTerminator() && I->getNumSuccessors() > 1)
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exploreSyncDependency(I);
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}
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exploreDataDependency(V);
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}
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}
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} // namespace
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// Register this pass.
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char LegacyDivergenceAnalysis::ID = 0;
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LegacyDivergenceAnalysis::LegacyDivergenceAnalysis() : FunctionPass(ID) {
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initializeLegacyDivergenceAnalysisPass(*PassRegistry::getPassRegistry());
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}
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INITIALIZE_PASS_BEGIN(LegacyDivergenceAnalysis, "divergence",
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"Legacy Divergence Analysis", false, true)
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INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
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INITIALIZE_PASS_DEPENDENCY(PostDominatorTreeWrapperPass)
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INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
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INITIALIZE_PASS_END(LegacyDivergenceAnalysis, "divergence",
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"Legacy Divergence Analysis", false, true)
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FunctionPass *llvm::createLegacyDivergenceAnalysisPass() {
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return new LegacyDivergenceAnalysis();
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}
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void LegacyDivergenceAnalysis::getAnalysisUsage(AnalysisUsage &AU) const {
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AU.addRequiredTransitive<DominatorTreeWrapperPass>();
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AU.addRequiredTransitive<PostDominatorTreeWrapperPass>();
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AU.addRequiredTransitive<LoopInfoWrapperPass>();
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AU.setPreservesAll();
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}
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bool LegacyDivergenceAnalysis::shouldUseGPUDivergenceAnalysis(
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const Function &F, const TargetTransformInfo &TTI) const {
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if (!(UseGPUDA || TTI.useGPUDivergenceAnalysis()))
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return false;
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// GPUDivergenceAnalysis requires a reducible CFG.
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auto &LI = getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
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using RPOTraversal = ReversePostOrderTraversal<const Function *>;
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RPOTraversal FuncRPOT(&F);
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return !containsIrreducibleCFG<const BasicBlock *, const RPOTraversal,
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const LoopInfo>(FuncRPOT, LI);
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}
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bool LegacyDivergenceAnalysis::runOnFunction(Function &F) {
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auto *TTIWP = getAnalysisIfAvailable<TargetTransformInfoWrapperPass>();
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if (TTIWP == nullptr)
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return false;
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TargetTransformInfo &TTI = TTIWP->getTTI(F);
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// Fast path: if the target does not have branch divergence, we do not mark
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// any branch as divergent.
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if (!TTI.hasBranchDivergence())
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return false;
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DivergentValues.clear();
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DivergentUses.clear();
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gpuDA = nullptr;
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auto &DT = getAnalysis<DominatorTreeWrapperPass>().getDomTree();
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auto &PDT = getAnalysis<PostDominatorTreeWrapperPass>().getPostDomTree();
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if (shouldUseGPUDivergenceAnalysis(F, TTI)) {
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// run the new GPU divergence analysis
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auto &LI = getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
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gpuDA = std::make_unique<GPUDivergenceAnalysis>(F, DT, PDT, LI, TTI);
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} else {
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// run LLVM's existing DivergenceAnalysis
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DivergencePropagator DP(F, TTI, DT, PDT, DivergentValues, DivergentUses);
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DP.populateWithSourcesOfDivergence();
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DP.propagate();
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}
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LLVM_DEBUG(dbgs() << "\nAfter divergence analysis on " << F.getName()
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<< ":\n";
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print(dbgs(), F.getParent()));
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return false;
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}
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bool LegacyDivergenceAnalysis::isDivergent(const Value *V) const {
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if (gpuDA) {
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return gpuDA->isDivergent(*V);
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}
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return DivergentValues.count(V);
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}
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bool LegacyDivergenceAnalysis::isDivergentUse(const Use *U) const {
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if (gpuDA) {
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return gpuDA->isDivergentUse(*U);
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}
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return DivergentValues.count(U->get()) || DivergentUses.count(U);
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}
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void LegacyDivergenceAnalysis::print(raw_ostream &OS, const Module *) const {
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if ((!gpuDA || !gpuDA->hasDivergence()) && DivergentValues.empty())
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return;
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const Function *F = nullptr;
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if (!DivergentValues.empty()) {
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const Value *FirstDivergentValue = *DivergentValues.begin();
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if (const Argument *Arg = dyn_cast<Argument>(FirstDivergentValue)) {
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F = Arg->getParent();
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} else if (const Instruction *I =
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dyn_cast<Instruction>(FirstDivergentValue)) {
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F = I->getParent()->getParent();
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} else {
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llvm_unreachable("Only arguments and instructions can be divergent");
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}
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} else if (gpuDA) {
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F = &gpuDA->getFunction();
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}
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if (!F)
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return;
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// Dumps all divergent values in F, arguments and then instructions.
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for (auto &Arg : F->args()) {
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OS << (isDivergent(&Arg) ? "DIVERGENT: " : " ");
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OS << Arg << "\n";
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}
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// Iterate instructions using instructions() to ensure a deterministic order.
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for (auto BI = F->begin(), BE = F->end(); BI != BE; ++BI) {
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auto &BB = *BI;
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OS << "\n " << BB.getName() << ":\n";
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for (auto &I : BB.instructionsWithoutDebug()) {
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OS << (isDivergent(&I) ? "DIVERGENT: " : " ");
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OS << I << "\n";
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}
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}
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OS << "\n";
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}
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