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-rw-r--r--llvm/lib/Transforms/Scalar/LoopUnrollPass.cpp217
1 files changed, 111 insertions, 106 deletions
diff --git a/llvm/lib/Transforms/Scalar/LoopUnrollPass.cpp b/llvm/lib/Transforms/Scalar/LoopUnrollPass.cpp
index 7bd1fcffbd5..3d2ae3a5b61 100644
--- a/llvm/lib/Transforms/Scalar/LoopUnrollPass.cpp
+++ b/llvm/lib/Transforms/Scalar/LoopUnrollPass.cpp
@@ -414,41 +414,39 @@ namespace {
// v = b[0]* 0 + b[1]* 1 + b[2]* 0
// And finally:
// v = b[1]
-class UnrollAnalyzer : public InstVisitor<UnrollAnalyzer, bool> {
- typedef InstVisitor<UnrollAnalyzer, bool> Base;
- friend class InstVisitor<UnrollAnalyzer, bool>;
+class UnrolledInstAnalyzer : private InstVisitor<UnrolledInstAnalyzer, bool> {
+ typedef InstVisitor<UnrolledInstAnalyzer, bool> Base;
+ friend class InstVisitor<UnrolledInstAnalyzer, bool>;
- /// \brief The loop we're going to analyze.
- const Loop *L;
+public:
+ UnrolledInstAnalyzer(unsigned Iteration,
+ DenseMap<Value *, Constant *> &SimplifiedValues,
+ SmallDenseMap<Value *, SCEVGEPDescriptor> &SCEVGEPCache)
+ : Iteration(Iteration), SimplifiedValues(SimplifiedValues),
+ SCEVGEPCache(SCEVGEPCache) {}
- /// \brief TripCount of the given loop.
- unsigned TripCount;
+ // Allow access to the initial visit method.
+ using Base::visit;
- ScalarEvolution &SE;
-
- const TargetTransformInfo &TTI;
+private:
+ /// \brief Number of currently simulated iteration.
+ ///
+ /// If an expression is ConstAddress+Constant, then the Constant is
+ /// Start + Iteration*Step, where Start and Step could be obtained from
+ /// SCEVGEPCache.
+ unsigned Iteration;
// While we walk the loop instructions, we we build up and maintain a mapping
// of simplified values specific to this iteration. The idea is to propagate
// any special information we have about loads that can be replaced with
// constants after complete unrolling, and account for likely simplifications
// post-unrolling.
- DenseMap<Value *, Constant *> SimplifiedValues;
+ DenseMap<Value *, Constant *> &SimplifiedValues;
// To avoid requesting SCEV info on every iteration, request it once, and
// for each value that would become ConstAddress+Constant after loop
// unrolling, save the corresponding data.
- SmallDenseMap<Value *, SCEVGEPDescriptor> SCEVGEPCache;
-
- /// \brief Number of currently simulated iteration.
- ///
- /// If an expression is ConstAddress+Constant, then the Constant is
- /// Start + Iteration*Step, where Start and Step could be obtained from
- /// SCEVGEPCache.
- unsigned Iteration;
-
- /// \brief Upper threshold for complete unrolling.
- unsigned MaxUnrolledLoopSize;
+ SmallDenseMap<Value *, SCEVGEPDescriptor> &SCEVGEPCache;
/// Base case for the instruction visitor.
bool visitInstruction(Instruction &I) { return false; };
@@ -524,95 +522,102 @@ class UnrollAnalyzer : public InstVisitor<UnrollAnalyzer, bool> {
return true;
}
+};
+} // namespace
-public:
- UnrollAnalyzer(const Loop *L, unsigned TripCount, ScalarEvolution &SE,
- const TargetTransformInfo &TTI, unsigned MaxUnrolledLoopSize)
- : L(L), TripCount(TripCount), SE(SE), TTI(TTI),
- MaxUnrolledLoopSize(MaxUnrolledLoopSize),
- NumberOfOptimizedInstructions(0), UnrolledLoopSize(0) {}
+namespace {
+struct EstimatedUnrollCost {
/// \brief Count the number of optimized instructions.
unsigned NumberOfOptimizedInstructions;
/// \brief Count the total number of instructions.
unsigned UnrolledLoopSize;
+};
+}
- /// \brief Figure out if the loop is worth full unrolling.
- ///
- /// Complete loop unrolling can make some loads constant, and we need to know
- /// if that would expose any further optimization opportunities. This routine
- /// estimates this optimization. It assigns computed number of instructions,
- /// that potentially might be optimized away, to
- /// NumberOfOptimizedInstructions, and total number of instructions to
- /// UnrolledLoopSize (not counting blocks that won't be reached, if we were
- /// able to compute the condition).
- /// \returns false if we can't analyze the loop, or if we discovered that
- /// unrolling won't give anything. Otherwise, returns true.
- bool analyzeLoop() {
- SmallSetVector<BasicBlock *, 16> BBWorklist;
-
- // We want to be able to scale offsets by the trip count and add more
- // offsets to them without checking for overflows, and we already don't want
- // to analyze *massive* trip counts, so we force the max to be reasonably
- // small.
- assert(UnrollMaxIterationsCountToAnalyze < (INT_MAX / 2) &&
- "The unroll iterations max is too large!");
-
- // Don't simulate loops with a big or unknown tripcount
- if (!UnrollMaxIterationsCountToAnalyze || !TripCount ||
- TripCount > UnrollMaxIterationsCountToAnalyze)
- return false;
-
- // To avoid compute SCEV-expressions on every iteration, compute them once
- // and store interesting to us in SCEVGEPCache.
- SCEVGEPCache = buildSCEVGEPCache(*L, SE);
-
- // Simulate execution of each iteration of the loop counting instructions,
- // which would be simplified.
- // Since the same load will take different values on different iterations,
- // we literally have to go through all loop's iterations.
- for (Iteration = 0; Iteration < TripCount; ++Iteration) {
- SimplifiedValues.clear();
- BBWorklist.clear();
- BBWorklist.insert(L->getHeader());
- // Note that we *must not* cache the size, this loop grows the worklist.
- for (unsigned Idx = 0; Idx != BBWorklist.size(); ++Idx) {
- BasicBlock *BB = BBWorklist[Idx];
-
- // Visit all instructions in the given basic block and try to simplify
- // it. We don't change the actual IR, just count optimization
- // opportunities.
- for (Instruction &I : *BB) {
- UnrolledLoopSize += TTI.getUserCost(&I);
-
- // Visit the instruction to analyze its loop cost after unrolling,
- // and if the visitor returns true, then we can optimize this
- // instruction away.
- if (Base::visit(I))
- NumberOfOptimizedInstructions += TTI.getUserCost(&I);
-
- // If unrolled body turns out to be too big, bail out.
- if (UnrolledLoopSize - NumberOfOptimizedInstructions >
- MaxUnrolledLoopSize)
- return false;
- }
+/// \brief Figure out if the loop is worth full unrolling.
+///
+/// Complete loop unrolling can make some loads constant, and we need to know
+/// if that would expose any further optimization opportunities. This routine
+/// estimates this optimization. It assigns computed number of instructions,
+/// that potentially might be optimized away, to
+/// NumberOfOptimizedInstructions, and total number of instructions to
+/// UnrolledLoopSize (not counting blocks that won't be reached, if we were
+/// able to compute the condition).
+/// \returns false if we can't analyze the loop, or if we discovered that
+/// unrolling won't give anything. Otherwise, returns true.
+Optional<EstimatedUnrollCost>
+analyzeLoopUnrollCost(const Loop *L, unsigned TripCount, ScalarEvolution &SE,
+ const TargetTransformInfo &TTI,
+ unsigned MaxUnrolledLoopSize) {
+ // We want to be able to scale offsets by the trip count and add more offsets
+ // to them without checking for overflows, and we already don't want to
+ // analyze *massive* trip counts, so we force the max to be reasonably small.
+ assert(UnrollMaxIterationsCountToAnalyze < (INT_MAX / 2) &&
+ "The unroll iterations max is too large!");
+
+ // Don't simulate loops with a big or unknown tripcount
+ if (!UnrollMaxIterationsCountToAnalyze || !TripCount ||
+ TripCount > UnrollMaxIterationsCountToAnalyze)
+ return None;
+
+ // To avoid compute SCEV-expressions on every iteration, compute them once
+ // and store interesting to us in SCEVGEPCache.
+ SmallDenseMap<Value *, SCEVGEPDescriptor> SCEVGEPCache =
+ buildSCEVGEPCache(*L, SE);
+
+ SmallSetVector<BasicBlock *, 16> BBWorklist;
+ DenseMap<Value *, Constant *> SimplifiedValues;
- // Add BB's successors to the worklist.
- for (BasicBlock *Succ : successors(BB))
- if (L->contains(Succ))
- BBWorklist.insert(Succ);
+ unsigned NumberOfOptimizedInstructions = 0;
+ unsigned UnrolledLoopSize = 0;
+
+ // Simulate execution of each iteration of the loop counting instructions,
+ // which would be simplified.
+ // Since the same load will take different values on different iterations,
+ // we literally have to go through all loop's iterations.
+ for (unsigned Iteration = 0; Iteration < TripCount; ++Iteration) {
+ SimplifiedValues.clear();
+ UnrolledInstAnalyzer Analyzer(Iteration, SimplifiedValues, SCEVGEPCache);
+
+ BBWorklist.clear();
+ BBWorklist.insert(L->getHeader());
+ // Note that we *must not* cache the size, this loop grows the worklist.
+ for (unsigned Idx = 0; Idx != BBWorklist.size(); ++Idx) {
+ BasicBlock *BB = BBWorklist[Idx];
+
+ // Visit all instructions in the given basic block and try to simplify
+ // it. We don't change the actual IR, just count optimization
+ // opportunities.
+ for (Instruction &I : *BB) {
+ UnrolledLoopSize += TTI.getUserCost(&I);
+
+ // Visit the instruction to analyze its loop cost after unrolling,
+ // and if the visitor returns true, then we can optimize this
+ // instruction away.
+ if (Analyzer.visit(I))
+ NumberOfOptimizedInstructions += TTI.getUserCost(&I);
+
+ // If unrolled body turns out to be too big, bail out.
+ if (UnrolledLoopSize - NumberOfOptimizedInstructions >
+ MaxUnrolledLoopSize)
+ return None;
}
- // If we found no optimization opportunities on the first iteration, we
- // won't find them on later ones too.
- if (!NumberOfOptimizedInstructions)
- return false;
+ // Add BB's successors to the worklist.
+ for (BasicBlock *Succ : successors(BB))
+ if (L->contains(Succ))
+ BBWorklist.insert(Succ);
}
- return true;
+
+ // If we found no optimization opportunities on the first iteration, we
+ // won't find them on later ones too.
+ if (!NumberOfOptimizedInstructions)
+ return None;
}
-};
-} // namespace
+ return {{NumberOfOptimizedInstructions, UnrolledLoopSize}};
+}
/// ApproximateLoopSize - Approximate the size of the loop.
static unsigned ApproximateLoopSize(const Loop *L, unsigned &NumCalls,
@@ -886,14 +891,14 @@ bool LoopUnroll::runOnLoop(Loop *L, LPPassManager &LPM) {
// The loop isn't that small, but we still can fully unroll it if that
// helps to remove a significant number of instructions.
// To check that, run additional analysis on the loop.
- UnrollAnalyzer UA(L, TripCount, *SE, TTI, AbsoluteThreshold);
- if (UA.analyzeLoop() &&
- canUnrollCompletely(L, Threshold, AbsoluteThreshold,
- UA.UnrolledLoopSize,
- UA.NumberOfOptimizedInstructions,
- PercentOfOptimizedForCompleteUnroll)) {
- Unrolling = Full;
- }
+ if (Optional<EstimatedUnrollCost> Cost =
+ analyzeLoopUnrollCost(L, TripCount, *SE, TTI, AbsoluteThreshold))
+ if (canUnrollCompletely(L, Threshold, AbsoluteThreshold,
+ Cost->UnrolledLoopSize,
+ Cost->NumberOfOptimizedInstructions,
+ PercentOfOptimizedForCompleteUnroll)) {
+ Unrolling = Full;
+ }
}
} else if (TripCount && Count < TripCount) {
Unrolling = Partial;
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