Adds an optional filtering control function to the dataflow solver's
initializeAndRun callback, which controls which analyses will be
initialized when running the solver. This makes it possible to reuse
existing dataflow solver instances that have already run to a fixpoint
without re-initializing all of the analyses that have already converged.
A new analysis and test pass is also added, which illustrates how the
filtering can be useful to run a staged analysis, which would not have
been possible before. The example analysis, called `BarAnalysis`,
depends on the converged state of the `FooAnalysis`. The Bar analysis is
a forward analysis that tracks, for each program point, whether any of
the preceding program points hold a `foo_state` that is divisible by 4.
In the example test, the control flow graph looks like the following:
```
entry-block
/ \
bb0 bb2
\ /
bb1
```
The `foo_state` of `bb1` depends on the `foo_state` of `bb0` and `bb2`.
If the solver goes through `bb0->bb1` before `bb2->bb1`, then there is
an intermediate stage in the analyses where the state of `bb1` could be
divisible by 4, even though the final state of `bb1` will not be
divisible by 4 in the converged state. If the `BarAnalysis` runs on
`bb1` in this intermediate state, then it will get stuck with the
"divisible by 4" state, and the analysis will not yield the desired
results.
This PR ensures that the `BarAnalysis` will see the correct state
`foo_state`, because the `FooAnalysis` will fully run to a fixpoint
before the `BarAnalysis` is loaded, initialized, and run.
The Foo and Bar analyses are just trivial examples, but this pattern is
useful when there are analyses that can be made more effective by using
complementary analyses like integer range/divisibility analyses.
**Note for integration:**
DataFlowSolver::load now stores the concrete analysis TypeID, exposed
via DataFlowAnalysis::getTypeID(). Downstream DataFlowAnalysis
subclasses defined in anonymous namespaces must add
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(ClassName) to their class
body.
Assisted-by: Codex (gpt-5.4)
909 lines
34 KiB
C++
909 lines
34 KiB
C++
//===- StackArrays.cpp ----------------------------------------------------===//
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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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#include "flang/Optimizer/Builder/FIRBuilder.h"
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#include "flang/Optimizer/Builder/LowLevelIntrinsics.h"
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#include "flang/Optimizer/Dialect/FIRAttr.h"
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#include "flang/Optimizer/Dialect/FIRDialect.h"
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#include "flang/Optimizer/Dialect/FIROps.h"
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#include "flang/Optimizer/Dialect/FIRType.h"
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#include "flang/Optimizer/Dialect/Support/FIRContext.h"
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#include "flang/Optimizer/Support/DataLayout.h"
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#include "flang/Optimizer/Transforms/Passes.h"
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#include "mlir/Analysis/DataFlow/ConstantPropagationAnalysis.h"
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#include "mlir/Analysis/DataFlow/DeadCodeAnalysis.h"
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#include "mlir/Analysis/DataFlow/DenseAnalysis.h"
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#include "mlir/Analysis/DataFlowFramework.h"
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#include "mlir/Dialect/DLTI/DLTI.h"
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#include "mlir/Dialect/Func/IR/FuncOps.h"
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#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
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#include "mlir/Dialect/OpenMP/OpenMPDialect.h"
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#include "mlir/IR/Builders.h"
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#include "mlir/IR/Diagnostics.h"
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#include "mlir/IR/Value.h"
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#include "mlir/Interfaces/LoopLikeInterface.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
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#include "mlir/Transforms/Passes.h"
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#include "llvm/ADT/DenseMap.h"
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#include "llvm/ADT/DenseSet.h"
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#include "llvm/ADT/PointerUnion.h"
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#include "llvm/Support/Casting.h"
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#include "llvm/Support/raw_ostream.h"
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#include <optional>
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namespace fir {
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#define GEN_PASS_DEF_STACKARRAYS
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#include "flang/Optimizer/Transforms/Passes.h.inc"
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} // namespace fir
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#define DEBUG_TYPE "stack-arrays"
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static llvm::cl::opt<std::size_t> maxAllocsPerFunc(
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"stack-arrays-max-allocs",
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llvm::cl::desc("The maximum number of heap allocations to consider in one "
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"function before skipping (to save compilation time). Set "
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"to 0 for no limit."),
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llvm::cl::init(1000), llvm::cl::Hidden);
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static llvm::cl::opt<bool> emitLifetimeMarkers(
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"stack-arrays-lifetime",
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llvm::cl::desc("Add lifetime markers to generated constant size allocas"),
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llvm::cl::init(false), llvm::cl::Hidden);
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namespace {
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/// The state of an SSA value at each program point
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enum class AllocationState {
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/// This means that the allocation state of a variable cannot be determined
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/// at this program point, e.g. because one route through a conditional freed
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/// the variable and the other route didn't.
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/// This asserts a known-unknown: different from the unknown-unknown of having
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/// no AllocationState stored for a particular SSA value
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Unknown,
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/// Means this SSA value was allocated on the heap in this function and has
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/// now been freed
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Freed,
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/// Means this SSA value was allocated on the heap in this function and is a
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/// candidate for moving to the stack
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Allocated,
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};
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/// Stores where an alloca should be inserted. If the PointerUnion is an
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/// Operation the alloca should be inserted /after/ the operation. If it is a
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/// block, the alloca can be placed anywhere in that block.
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class InsertionPoint {
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llvm::PointerUnion<mlir::Operation *, mlir::Block *> location;
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bool saveRestoreStack;
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/// Get contained pointer type or nullptr
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template <class T>
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T *tryGetPtr() const {
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// Use llvm::dyn_cast_if_present because location may be null here.
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if (T *ptr = llvm::dyn_cast_if_present<T *>(location))
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return ptr;
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return nullptr;
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}
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public:
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template <class T>
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InsertionPoint(T *ptr, bool saveRestoreStack = false)
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: location(ptr), saveRestoreStack{saveRestoreStack} {}
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InsertionPoint(std::nullptr_t null)
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: location(null), saveRestoreStack{false} {}
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/// Get contained operation, or nullptr
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mlir::Operation *tryGetOperation() const {
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return tryGetPtr<mlir::Operation>();
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}
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/// Get contained block, or nullptr
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mlir::Block *tryGetBlock() const { return tryGetPtr<mlir::Block>(); }
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/// Get whether the stack should be saved/restored. If yes, an llvm.stacksave
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/// intrinsic should be added before the alloca, and an llvm.stackrestore
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/// intrinsic should be added where the freemem is
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bool shouldSaveRestoreStack() const { return saveRestoreStack; }
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operator bool() const { return tryGetOperation() || tryGetBlock(); }
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bool operator==(const InsertionPoint &rhs) const {
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return (location == rhs.location) &&
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(saveRestoreStack == rhs.saveRestoreStack);
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}
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bool operator!=(const InsertionPoint &rhs) const { return !(*this == rhs); }
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};
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/// Maps SSA values to their AllocationState at a particular program point.
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/// Also caches the insertion points for the new alloca operations
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class LatticePoint : public mlir::dataflow::AbstractDenseLattice {
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// Maps all values we are interested in to states
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llvm::SmallDenseMap<mlir::Value, AllocationState, 1> stateMap;
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public:
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MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(LatticePoint)
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using AbstractDenseLattice::AbstractDenseLattice;
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bool operator==(const LatticePoint &rhs) const {
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return stateMap == rhs.stateMap;
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}
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/// Join the lattice accross control-flow edges
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mlir::ChangeResult join(const AbstractDenseLattice &lattice) override;
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void print(llvm::raw_ostream &os) const override;
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/// Clear all modifications
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mlir::ChangeResult reset();
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/// Set the state of an SSA value
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mlir::ChangeResult set(mlir::Value value, AllocationState state);
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/// Get fir.allocmem ops which were allocated in this function and always
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/// freed before the function returns, plus whre to insert replacement
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/// fir.alloca ops
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void appendFreedValues(llvm::DenseSet<mlir::Value> &out) const;
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std::optional<AllocationState> get(mlir::Value val) const;
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};
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class AllocationAnalysis
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: public mlir::dataflow::DenseForwardDataFlowAnalysis<LatticePoint> {
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public:
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MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(AllocationAnalysis)
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using DenseForwardDataFlowAnalysis::DenseForwardDataFlowAnalysis;
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mlir::LogicalResult visitOperation(mlir::Operation *op,
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const LatticePoint &before,
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LatticePoint *after) override;
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/// At an entry point, the last modifications of all memory resources are
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/// yet to be determined
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void setToEntryState(LatticePoint *lattice) override;
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protected:
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/// Visit control flow operations and decide whether to call visitOperation
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/// to apply the transfer function
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mlir::LogicalResult processOperation(mlir::Operation *op) override;
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};
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/// Drives analysis to find candidate fir.allocmem operations which could be
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/// moved to the stack. Intended to be used with mlir::Pass::getAnalysis
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class StackArraysAnalysisWrapper {
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public:
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MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(StackArraysAnalysisWrapper)
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// Maps fir.allocmem -> place to insert alloca
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using AllocMemMap = llvm::DenseMap<mlir::Operation *, InsertionPoint>;
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StackArraysAnalysisWrapper(mlir::Operation *op) {}
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// returns nullptr if analysis failed
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const AllocMemMap *getCandidateOps(mlir::Operation *func);
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private:
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llvm::DenseMap<mlir::Operation *, AllocMemMap> funcMaps;
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llvm::LogicalResult analyseFunction(mlir::Operation *func);
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};
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/// Converts a fir.allocmem to a fir.alloca
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class AllocMemConversion : public mlir::OpRewritePattern<fir::AllocMemOp> {
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public:
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explicit AllocMemConversion(
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mlir::MLIRContext *ctx,
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const StackArraysAnalysisWrapper::AllocMemMap &candidateOps,
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std::optional<mlir::DataLayout> &dl,
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std::optional<fir::KindMapping> &kindMap)
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: OpRewritePattern(ctx), candidateOps{candidateOps}, dl{dl},
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kindMap{kindMap} {}
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llvm::LogicalResult
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matchAndRewrite(fir::AllocMemOp allocmem,
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mlir::PatternRewriter &rewriter) const override;
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/// Determine where to insert the alloca operation. The returned value should
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/// be checked to see if it is inside a loop
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static InsertionPoint
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findAllocaInsertionPoint(fir::AllocMemOp &oldAlloc,
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const llvm::SmallVector<mlir::Operation *> &freeOps);
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private:
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/// Handle to the DFA (already run)
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const StackArraysAnalysisWrapper::AllocMemMap &candidateOps;
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const std::optional<mlir::DataLayout> &dl;
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const std::optional<fir::KindMapping> &kindMap;
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/// If we failed to find an insertion point not inside a loop, see if it would
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/// be safe to use an llvm.stacksave/llvm.stackrestore inside the loop
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static InsertionPoint findAllocaLoopInsertionPoint(
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fir::AllocMemOp &oldAlloc,
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const llvm::SmallVector<mlir::Operation *> &freeOps);
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/// Returns the alloca if it was successfully inserted, otherwise {}
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std::optional<fir::AllocaOp>
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insertAlloca(fir::AllocMemOp &oldAlloc,
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mlir::PatternRewriter &rewriter) const;
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/// Inserts a stacksave before oldAlloc and a stackrestore after each freemem
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void insertStackSaveRestore(fir::AllocMemOp oldAlloc,
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mlir::PatternRewriter &rewriter) const;
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/// Emit lifetime markers for newAlloc between oldAlloc and each freemem.
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/// If the allocation is dynamic, no life markers are emitted.
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void insertLifetimeMarkers(fir::AllocMemOp oldAlloc, fir::AllocaOp newAlloc,
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mlir::PatternRewriter &rewriter) const;
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};
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class StackArraysPass : public fir::impl::StackArraysBase<StackArraysPass> {
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public:
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StackArraysPass() = default;
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StackArraysPass(const StackArraysPass &pass);
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llvm::StringRef getDescription() const override;
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void runOnOperation() override;
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private:
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Statistic runCount{this, "stackArraysRunCount",
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"Number of heap allocations moved to the stack"};
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};
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} // namespace
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static void print(llvm::raw_ostream &os, AllocationState state) {
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switch (state) {
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case AllocationState::Unknown:
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os << "Unknown";
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break;
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case AllocationState::Freed:
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os << "Freed";
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break;
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case AllocationState::Allocated:
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os << "Allocated";
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break;
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}
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}
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/// Join two AllocationStates for the same value coming from different CFG
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/// blocks
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static AllocationState join(AllocationState lhs, AllocationState rhs) {
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// | Allocated | Freed | Unknown
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// ========= | ========= | ========= | =========
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// Allocated | Allocated | Unknown | Unknown
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// Freed | Unknown | Freed | Unknown
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// Unknown | Unknown | Unknown | Unknown
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if (lhs == rhs)
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return lhs;
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return AllocationState::Unknown;
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}
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mlir::ChangeResult LatticePoint::join(const AbstractDenseLattice &lattice) {
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const auto &rhs = static_cast<const LatticePoint &>(lattice);
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mlir::ChangeResult changed = mlir::ChangeResult::NoChange;
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// add everything from rhs to map, handling cases where values are in both
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for (const auto &[value, rhsState] : rhs.stateMap) {
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auto it = stateMap.find(value);
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if (it != stateMap.end()) {
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// value is present in both maps
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AllocationState myState = it->second;
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AllocationState newState = ::join(myState, rhsState);
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if (newState != myState) {
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changed = mlir::ChangeResult::Change;
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it->getSecond() = newState;
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}
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} else {
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// value not present in current map: add it
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stateMap.insert({value, rhsState});
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changed = mlir::ChangeResult::Change;
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}
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}
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return changed;
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}
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void LatticePoint::print(llvm::raw_ostream &os) const {
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for (const auto &[value, state] : stateMap) {
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os << "\n * " << value << ": ";
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::print(os, state);
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}
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}
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mlir::ChangeResult LatticePoint::reset() {
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if (stateMap.empty())
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return mlir::ChangeResult::NoChange;
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stateMap.clear();
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return mlir::ChangeResult::Change;
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}
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mlir::ChangeResult LatticePoint::set(mlir::Value value, AllocationState state) {
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if (stateMap.count(value)) {
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// already in map
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AllocationState &oldState = stateMap[value];
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if (oldState != state) {
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stateMap[value] = state;
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return mlir::ChangeResult::Change;
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}
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return mlir::ChangeResult::NoChange;
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}
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stateMap.insert({value, state});
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return mlir::ChangeResult::Change;
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}
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/// Get values which were allocated in this function and always freed before
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/// the function returns
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void LatticePoint::appendFreedValues(llvm::DenseSet<mlir::Value> &out) const {
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for (auto &[value, state] : stateMap) {
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if (state == AllocationState::Freed)
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out.insert(value);
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}
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}
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std::optional<AllocationState> LatticePoint::get(mlir::Value val) const {
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auto it = stateMap.find(val);
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if (it == stateMap.end())
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return {};
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return it->second;
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}
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static mlir::Value lookThroughDeclaresAndConverts(mlir::Value value) {
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while (mlir::Operation *op = value.getDefiningOp()) {
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if (auto declareOp = llvm::dyn_cast<fir::DeclareOp>(op))
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value = declareOp.getMemref();
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else if (auto convertOp = llvm::dyn_cast<fir::ConvertOp>(op))
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value = convertOp->getOperand(0);
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else
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return value;
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}
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return value;
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}
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mlir::LogicalResult AllocationAnalysis::visitOperation(
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mlir::Operation *op, const LatticePoint &before, LatticePoint *after) {
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LLVM_DEBUG(llvm::dbgs() << "StackArrays: Visiting operation: " << *op
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<< "\n");
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LLVM_DEBUG(llvm::dbgs() << "--Lattice in: " << before << "\n");
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// propagate before -> after
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mlir::ChangeResult changed = after->join(before);
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if (auto allocmem = mlir::dyn_cast<fir::AllocMemOp>(op)) {
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assert(op->getNumResults() == 1 && "fir.allocmem has one result");
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auto attr = op->getAttrOfType<fir::MustBeHeapAttr>(
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fir::MustBeHeapAttr::getAttrName());
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if (attr && attr.getValue()) {
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LLVM_DEBUG(llvm::dbgs() << "--Found fir.must_be_heap: skipping\n");
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// skip allocation marked not to be moved
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return mlir::success();
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}
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auto retTy = allocmem.getAllocatedType();
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if (!mlir::isa<fir::SequenceType>(retTy)) {
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LLVM_DEBUG(llvm::dbgs()
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<< "--Allocation is not for an array: skipping\n");
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return mlir::success();
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}
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mlir::Value result = op->getResult(0);
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changed |= after->set(result, AllocationState::Allocated);
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} else if (mlir::isa<fir::FreeMemOp>(op)) {
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assert(op->getNumOperands() == 1 && "fir.freemem has one operand");
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mlir::Value operand = op->getOperand(0);
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// Note: StackArrays is scheduled in the pass pipeline after lowering hlfir
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// to fir. Therefore, we only need to handle `fir::DeclareOp`s. Also look
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// past converts in case the pointer was changed between different pointer
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// types.
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operand = lookThroughDeclaresAndConverts(operand);
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std::optional<AllocationState> operandState = before.get(operand);
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if (operandState && *operandState == AllocationState::Allocated) {
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// don't tag things not allocated in this function as freed, so that we
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// don't think they are candidates for moving to the stack
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changed |= after->set(operand, AllocationState::Freed);
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}
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} else if (mlir::isa<fir::ResultOp>(op)) {
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mlir::Operation *parent = op->getParentOp();
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LatticePoint *parentLattice = getLattice(getProgramPointAfter(parent));
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assert(parentLattice);
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mlir::ChangeResult parentChanged = parentLattice->join(*after);
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propagateIfChanged(parentLattice, parentChanged);
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}
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// we pass lattices straight through fir.call because called functions should
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// not deallocate flang-generated array temporaries
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LLVM_DEBUG(llvm::dbgs() << "--Lattice out: " << *after << "\n");
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propagateIfChanged(after, changed);
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return mlir::success();
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}
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void AllocationAnalysis::setToEntryState(LatticePoint *lattice) {
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propagateIfChanged(lattice, lattice->reset());
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}
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/// Mostly a copy of AbstractDenseLattice::processOperation - the difference
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/// being that call operations are passed through to the transfer function
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mlir::LogicalResult AllocationAnalysis::processOperation(mlir::Operation *op) {
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mlir::ProgramPoint *point = getProgramPointAfter(op);
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// If the containing block is not executable, bail out.
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if (op->getBlock() != nullptr &&
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!getOrCreateFor<mlir::dataflow::Executable>(
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point, getProgramPointBefore(op->getBlock()))
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->isLive())
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|
return mlir::success();
|
|
|
|
// Get the dense lattice to update
|
|
mlir::dataflow::AbstractDenseLattice *after = getLattice(point);
|
|
|
|
// If this op implements region control-flow, then control-flow dictates its
|
|
// transfer function.
|
|
if (auto branch = mlir::dyn_cast<mlir::RegionBranchOpInterface>(op)) {
|
|
visitRegionBranchOperation(point, branch, after);
|
|
return mlir::success();
|
|
}
|
|
|
|
// pass call operations through to the transfer function
|
|
|
|
// Get the dense state before the execution of the op.
|
|
const mlir::dataflow::AbstractDenseLattice *before =
|
|
getLatticeFor(point, getProgramPointBefore(op));
|
|
|
|
/// Invoke the operation transfer function
|
|
return visitOperationImpl(op, *before, after);
|
|
}
|
|
|
|
llvm::LogicalResult
|
|
StackArraysAnalysisWrapper::analyseFunction(mlir::Operation *func) {
|
|
assert(mlir::isa<mlir::func::FuncOp>(func));
|
|
size_t nAllocs = 0;
|
|
func->walk([&nAllocs](fir::AllocMemOp) { nAllocs++; });
|
|
// don't bother with the analysis if there are no heap allocations
|
|
if (nAllocs == 0)
|
|
return mlir::success();
|
|
if ((maxAllocsPerFunc != 0) && (nAllocs > maxAllocsPerFunc)) {
|
|
LLVM_DEBUG(llvm::dbgs() << "Skipping stack arrays for function with "
|
|
<< nAllocs << " heap allocations");
|
|
return mlir::success();
|
|
}
|
|
|
|
mlir::DataFlowSolver solver;
|
|
// constant propagation is required for dead code analysis, dead code analysis
|
|
// is required to mark blocks live (required for mlir dense dfa)
|
|
solver.load<mlir::dataflow::SparseConstantPropagation>();
|
|
solver.load<mlir::dataflow::DeadCodeAnalysis>();
|
|
|
|
auto [it, inserted] = funcMaps.try_emplace(func);
|
|
AllocMemMap &candidateOps = it->second;
|
|
|
|
solver.load<AllocationAnalysis>();
|
|
if (failed(solver.initializeAndRun(func))) {
|
|
llvm::errs() << "DataFlowSolver failed!";
|
|
return mlir::failure();
|
|
}
|
|
|
|
LatticePoint point{solver.getProgramPointAfter(func)};
|
|
auto joinOperationLattice = [&](mlir::Operation *op) {
|
|
const LatticePoint *lattice =
|
|
solver.lookupState<LatticePoint>(solver.getProgramPointAfter(op));
|
|
// there will be no lattice for an unreachable block
|
|
if (lattice)
|
|
(void)point.join(*lattice);
|
|
};
|
|
|
|
func->walk([&](mlir::func::ReturnOp child) { joinOperationLattice(child); });
|
|
func->walk([&](fir::UnreachableOp child) { joinOperationLattice(child); });
|
|
func->walk(
|
|
[&](mlir::omp::TerminatorOp child) { joinOperationLattice(child); });
|
|
func->walk([&](mlir::omp::YieldOp child) { joinOperationLattice(child); });
|
|
|
|
llvm::DenseSet<mlir::Value> freedValues;
|
|
point.appendFreedValues(freedValues);
|
|
|
|
// Find all fir.freemem operations corresponding to fir.allocmem
|
|
// in freedValues. It is best to find the association going back
|
|
// from fir.freemem to fir.allocmem through the def-use chains,
|
|
// so that we can use lookThroughDeclaresAndConverts same way
|
|
// the AllocationAnalysis is handling them.
|
|
llvm::DenseMap<mlir::Operation *, llvm::SmallVector<mlir::Operation *>>
|
|
allocToFreeMemMap;
|
|
func->walk([&](fir::FreeMemOp freeOp) {
|
|
mlir::Value memref = lookThroughDeclaresAndConverts(freeOp.getHeapref());
|
|
if (!freedValues.count(memref))
|
|
return;
|
|
|
|
auto allocMem = memref.getDefiningOp<fir::AllocMemOp>();
|
|
allocToFreeMemMap[allocMem].push_back(freeOp);
|
|
});
|
|
|
|
// We only replace allocations which are definately freed on all routes
|
|
// through the function because otherwise the allocation may have an intende
|
|
// lifetime longer than the current stack frame (e.g. a heap allocation which
|
|
// is then freed by another function).
|
|
for (mlir::Value freedValue : freedValues) {
|
|
fir::AllocMemOp allocmem = freedValue.getDefiningOp<fir::AllocMemOp>();
|
|
InsertionPoint insertionPoint =
|
|
AllocMemConversion::findAllocaInsertionPoint(
|
|
allocmem, allocToFreeMemMap[allocmem]);
|
|
if (insertionPoint)
|
|
candidateOps.insert({allocmem, insertionPoint});
|
|
}
|
|
|
|
LLVM_DEBUG(for (auto [allocMemOp, _] : candidateOps) {
|
|
llvm::dbgs() << "StackArrays: Found candidate op: " << *allocMemOp << '\n';
|
|
});
|
|
return mlir::success();
|
|
}
|
|
|
|
const StackArraysAnalysisWrapper::AllocMemMap *
|
|
StackArraysAnalysisWrapper::getCandidateOps(mlir::Operation *func) {
|
|
if (!funcMaps.contains(func))
|
|
if (mlir::failed(analyseFunction(func)))
|
|
return nullptr;
|
|
return &funcMaps[func];
|
|
}
|
|
|
|
/// Restore the old allocation type exected by existing code
|
|
static mlir::Value convertAllocationType(mlir::PatternRewriter &rewriter,
|
|
const mlir::Location &loc,
|
|
mlir::Value heap, mlir::Value stack) {
|
|
mlir::Type heapTy = heap.getType();
|
|
mlir::Type stackTy = stack.getType();
|
|
|
|
if (heapTy == stackTy)
|
|
return stack;
|
|
|
|
fir::HeapType firHeapTy = mlir::cast<fir::HeapType>(heapTy);
|
|
[[maybe_unused]] fir::ReferenceType firRefTy =
|
|
mlir::cast<fir::ReferenceType>(stackTy);
|
|
assert(firHeapTy.getElementType() == firRefTy.getElementType() &&
|
|
"Allocations must have the same type");
|
|
|
|
auto insertionPoint = rewriter.saveInsertionPoint();
|
|
rewriter.setInsertionPointAfter(stack.getDefiningOp());
|
|
mlir::Value conv =
|
|
fir::ConvertOp::create(rewriter, loc, firHeapTy, stack).getResult();
|
|
rewriter.restoreInsertionPoint(insertionPoint);
|
|
return conv;
|
|
}
|
|
|
|
llvm::LogicalResult
|
|
AllocMemConversion::matchAndRewrite(fir::AllocMemOp allocmem,
|
|
mlir::PatternRewriter &rewriter) const {
|
|
auto oldInsertionPt = rewriter.saveInsertionPoint();
|
|
// add alloca operation
|
|
std::optional<fir::AllocaOp> alloca = insertAlloca(allocmem, rewriter);
|
|
rewriter.restoreInsertionPoint(oldInsertionPt);
|
|
if (!alloca)
|
|
return mlir::failure();
|
|
|
|
// remove freemem operations
|
|
llvm::SmallVector<mlir::Operation *> erases;
|
|
mlir::Operation *parent = allocmem->getParentOp();
|
|
// TODO: this shouldn't need to be re-calculated for every allocmem
|
|
parent->walk([&](fir::FreeMemOp freeOp) {
|
|
if (lookThroughDeclaresAndConverts(freeOp->getOperand(0)) == allocmem)
|
|
erases.push_back(freeOp);
|
|
});
|
|
|
|
// now we are done iterating the users, it is safe to mutate them
|
|
for (mlir::Operation *erase : erases)
|
|
rewriter.eraseOp(erase);
|
|
|
|
// replace references to heap allocation with references to stack allocation
|
|
mlir::Value newValue = convertAllocationType(
|
|
rewriter, allocmem.getLoc(), allocmem.getResult(), alloca->getResult());
|
|
rewriter.replaceOp(allocmem, newValue);
|
|
|
|
return mlir::success();
|
|
}
|
|
|
|
static bool isInLoop(mlir::Block *block) {
|
|
return mlir::LoopLikeOpInterface::blockIsInLoop(block);
|
|
}
|
|
|
|
static bool isInLoop(mlir::Operation *op) {
|
|
return isInLoop(op->getBlock()) ||
|
|
op->getParentOfType<mlir::LoopLikeOpInterface>();
|
|
}
|
|
|
|
InsertionPoint AllocMemConversion::findAllocaInsertionPoint(
|
|
fir::AllocMemOp &oldAlloc,
|
|
const llvm::SmallVector<mlir::Operation *> &freeOps) {
|
|
// Ideally the alloca should be inserted at the end of the function entry
|
|
// block so that we do not allocate stack space in a loop. However,
|
|
// the operands to the alloca may not be available that early, so insert it
|
|
// after the last operand becomes available
|
|
// If the old allocmem op was in an openmp region then it should not be moved
|
|
// outside of that
|
|
LLVM_DEBUG(llvm::dbgs() << "StackArrays: findAllocaInsertionPoint: "
|
|
<< oldAlloc << "\n");
|
|
|
|
// check that an Operation or Block we are about to return is not in a loop
|
|
auto checkReturn = [&](auto *point) -> InsertionPoint {
|
|
if (isInLoop(point)) {
|
|
mlir::Operation *oldAllocOp = oldAlloc.getOperation();
|
|
if (isInLoop(oldAllocOp)) {
|
|
// where we want to put it is in a loop, and even the old location is in
|
|
// a loop. Give up.
|
|
return findAllocaLoopInsertionPoint(oldAlloc, freeOps);
|
|
}
|
|
return {oldAllocOp};
|
|
}
|
|
return {point};
|
|
};
|
|
|
|
auto oldOmpRegion =
|
|
oldAlloc->getParentOfType<mlir::omp::OutlineableOpenMPOpInterface>();
|
|
|
|
// Find when the last operand value becomes available
|
|
mlir::Block *operandsBlock = nullptr;
|
|
mlir::Operation *lastOperand = nullptr;
|
|
for (mlir::Value operand : oldAlloc.getOperands()) {
|
|
LLVM_DEBUG(llvm::dbgs() << "--considering operand " << operand << "\n");
|
|
mlir::Operation *op = operand.getDefiningOp();
|
|
if (!op)
|
|
return checkReturn(oldAlloc.getOperation());
|
|
if (!operandsBlock)
|
|
operandsBlock = op->getBlock();
|
|
else if (operandsBlock != op->getBlock()) {
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< "----operand declared in a different block!\n");
|
|
// Operation::isBeforeInBlock requires the operations to be in the same
|
|
// block. The best we can do is the location of the allocmem.
|
|
return checkReturn(oldAlloc.getOperation());
|
|
}
|
|
if (!lastOperand || lastOperand->isBeforeInBlock(op))
|
|
lastOperand = op;
|
|
}
|
|
|
|
if (lastOperand) {
|
|
// There were value operands to the allocmem so insert after the last one
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< "--Placing after last operand: " << *lastOperand << "\n");
|
|
// Check we aren't moving across a stackrestore scope boundary.
|
|
// The last operand may have been defined in an earlier stacksave/
|
|
// stackrestore scope. Placing the alloca at the operand's location would
|
|
// put it in the wrong scope, causing it to get reclaimed before its
|
|
// actual use.
|
|
//
|
|
// To start, we find the ancestor of oldAlloc that resides in lastOperand's
|
|
// block. If oldAlloc is in the same block, this is oldAlloc itself.
|
|
// If oldAlloc is nested in a region, this is the enclosing op in
|
|
// lastOperand's block. If no such ancestor exists (e.g. the blocks are
|
|
// siblings), conservatively fall back to the allocmem's own location.
|
|
mlir::Operation *target = oldAlloc.getOperation();
|
|
while (target && target->getBlock() != lastOperand->getBlock())
|
|
target = target->getParentOp();
|
|
if (!target) {
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< "--Cannot find allocmem ancestor in lastOperand's "
|
|
"block, falling back to allocmem location\n");
|
|
return checkReturn(oldAlloc.getOperation());
|
|
}
|
|
|
|
// Walk from lastOperand to target in the same block, checking for
|
|
// stackrestore ops. We do not descend into regions of intervening
|
|
// operations; a stackrestore inside a region is expected to be paired
|
|
// with its own stacksave and does not affect the enclosing scope.
|
|
for (mlir::Operation *op = lastOperand->getNextNode(); op && op != target;
|
|
op = op->getNextNode()) {
|
|
if (mlir::isa<mlir::LLVM::StackRestoreOp>(op)) {
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< "--stackrestore found between lastOperand and "
|
|
"allocmem, falling back to allocmem location\n");
|
|
return checkReturn(oldAlloc.getOperation());
|
|
}
|
|
}
|
|
|
|
// check we aren't moving out of an omp region
|
|
auto lastOpOmpRegion =
|
|
lastOperand->getParentOfType<mlir::omp::OutlineableOpenMPOpInterface>();
|
|
if (lastOpOmpRegion == oldOmpRegion)
|
|
return checkReturn(lastOperand);
|
|
|
|
// Presumably this happened because the operands became ready before the
|
|
// start of this openmp region. (lastOpOmpRegion != oldOmpRegion) should
|
|
// imply that oldOmpRegion comes after lastOpOmpRegion.
|
|
return checkReturn(oldOmpRegion.getAllocaBlock());
|
|
}
|
|
|
|
// There were no value operands to the allocmem so we are safe to insert it
|
|
// as early as we want
|
|
|
|
// handle openmp case
|
|
if (oldOmpRegion)
|
|
return checkReturn(oldOmpRegion.getAllocaBlock());
|
|
|
|
// fall back to the function entry block
|
|
mlir::func::FuncOp func = oldAlloc->getParentOfType<mlir::func::FuncOp>();
|
|
assert(func && "This analysis is run on func.func");
|
|
mlir::Block &entryBlock = func.getBlocks().front();
|
|
LLVM_DEBUG(llvm::dbgs() << "--Placing at the start of func entry block\n");
|
|
return checkReturn(&entryBlock);
|
|
}
|
|
|
|
InsertionPoint AllocMemConversion::findAllocaLoopInsertionPoint(
|
|
fir::AllocMemOp &oldAlloc,
|
|
const llvm::SmallVector<mlir::Operation *> &freeOps) {
|
|
mlir::Operation *oldAllocOp = oldAlloc;
|
|
// This is only called as a last resort. We should try to insert at the
|
|
// location of the old allocation, which is inside of a loop, using
|
|
// llvm.stacksave/llvm.stackrestore
|
|
|
|
assert(freeOps.size() && "DFA should only return freed memory");
|
|
|
|
// Don't attempt to reason about a stacksave/stackrestore between different
|
|
// blocks
|
|
for (mlir::Operation *free : freeOps)
|
|
if (free->getBlock() != oldAllocOp->getBlock())
|
|
return {nullptr};
|
|
|
|
// Check that there aren't any other stack allocations in between the
|
|
// stack save and stack restore
|
|
// note: for flang generated temporaries there should only be one free op
|
|
for (mlir::Operation *free : freeOps) {
|
|
for (mlir::Operation *op = oldAlloc; op && op != free;
|
|
op = op->getNextNode()) {
|
|
if (mlir::isa<fir::AllocaOp>(op))
|
|
return {nullptr};
|
|
}
|
|
}
|
|
|
|
return InsertionPoint{oldAllocOp, /*shouldStackSaveRestore=*/true};
|
|
}
|
|
|
|
std::optional<fir::AllocaOp>
|
|
AllocMemConversion::insertAlloca(fir::AllocMemOp &oldAlloc,
|
|
mlir::PatternRewriter &rewriter) const {
|
|
auto it = candidateOps.find(oldAlloc.getOperation());
|
|
if (it == candidateOps.end())
|
|
return {};
|
|
InsertionPoint insertionPoint = it->second;
|
|
if (!insertionPoint)
|
|
return {};
|
|
|
|
if (insertionPoint.shouldSaveRestoreStack())
|
|
insertStackSaveRestore(oldAlloc, rewriter);
|
|
|
|
mlir::Location loc = oldAlloc.getLoc();
|
|
mlir::Type varTy = oldAlloc.getInType();
|
|
if (mlir::Operation *op = insertionPoint.tryGetOperation()) {
|
|
rewriter.setInsertionPointAfter(op);
|
|
} else {
|
|
mlir::Block *block = insertionPoint.tryGetBlock();
|
|
assert(block && "There must be a valid insertion point");
|
|
rewriter.setInsertionPointToStart(block);
|
|
}
|
|
|
|
auto unpackName = [](std::optional<llvm::StringRef> opt) -> llvm::StringRef {
|
|
if (opt)
|
|
return *opt;
|
|
return {};
|
|
};
|
|
|
|
llvm::StringRef uniqName = unpackName(oldAlloc.getUniqName());
|
|
llvm::StringRef bindcName = unpackName(oldAlloc.getBindcName());
|
|
auto alloca =
|
|
fir::AllocaOp::create(rewriter, loc, varTy, uniqName, bindcName,
|
|
oldAlloc.getTypeparams(), oldAlloc.getShape());
|
|
if (emitLifetimeMarkers)
|
|
insertLifetimeMarkers(oldAlloc, alloca, rewriter);
|
|
|
|
return alloca;
|
|
}
|
|
|
|
static void
|
|
visitFreeMemOp(fir::AllocMemOp oldAlloc,
|
|
const std::function<void(mlir::Operation *)> &callBack) {
|
|
for (mlir::Operation *user : oldAlloc->getUsers()) {
|
|
if (auto declareOp = mlir::dyn_cast_if_present<fir::DeclareOp>(user)) {
|
|
for (mlir::Operation *user : declareOp->getUsers()) {
|
|
if (mlir::isa<fir::FreeMemOp>(user))
|
|
callBack(user);
|
|
}
|
|
}
|
|
|
|
if (mlir::isa<fir::FreeMemOp>(user))
|
|
callBack(user);
|
|
}
|
|
}
|
|
|
|
void AllocMemConversion::insertStackSaveRestore(
|
|
fir::AllocMemOp oldAlloc, mlir::PatternRewriter &rewriter) const {
|
|
mlir::OpBuilder::InsertionGuard insertGuard(rewriter);
|
|
auto mod = oldAlloc->getParentOfType<mlir::ModuleOp>();
|
|
fir::FirOpBuilder builder{rewriter, mod};
|
|
|
|
builder.setInsertionPoint(oldAlloc);
|
|
mlir::Value sp = builder.genStackSave(oldAlloc.getLoc());
|
|
|
|
auto createStackRestoreCall = [&](mlir::Operation *user) {
|
|
builder.setInsertionPoint(user);
|
|
builder.genStackRestore(user->getLoc(), sp);
|
|
};
|
|
visitFreeMemOp(oldAlloc, createStackRestoreCall);
|
|
}
|
|
|
|
void AllocMemConversion::insertLifetimeMarkers(
|
|
fir::AllocMemOp oldAlloc, fir::AllocaOp newAlloc,
|
|
mlir::PatternRewriter &rewriter) const {
|
|
if (!dl || !kindMap)
|
|
return;
|
|
llvm::StringRef attrName = fir::getHasLifetimeMarkerAttrName();
|
|
// Do not add lifetime markers if the alloca already has any.
|
|
if (newAlloc->hasAttr(attrName))
|
|
return;
|
|
if (std::optional<int64_t> size =
|
|
fir::getAllocaByteSize(newAlloc, *dl, *kindMap)) {
|
|
mlir::OpBuilder::InsertionGuard insertGuard(rewriter);
|
|
rewriter.setInsertionPoint(oldAlloc);
|
|
mlir::Value ptr = fir::factory::genLifetimeStart(
|
|
rewriter, newAlloc.getLoc(), newAlloc, &*dl);
|
|
visitFreeMemOp(oldAlloc, [&](mlir::Operation *op) {
|
|
rewriter.setInsertionPoint(op);
|
|
fir::factory::genLifetimeEnd(rewriter, op->getLoc(), ptr);
|
|
});
|
|
newAlloc->setAttr(attrName, rewriter.getUnitAttr());
|
|
}
|
|
}
|
|
|
|
StackArraysPass::StackArraysPass(const StackArraysPass &pass)
|
|
: fir::impl::StackArraysBase<StackArraysPass>(pass) {}
|
|
|
|
llvm::StringRef StackArraysPass::getDescription() const {
|
|
return "Move heap allocated array temporaries to the stack";
|
|
}
|
|
|
|
void StackArraysPass::runOnOperation() {
|
|
mlir::func::FuncOp func = getOperation();
|
|
|
|
auto &analysis = getAnalysis<StackArraysAnalysisWrapper>();
|
|
const StackArraysAnalysisWrapper::AllocMemMap *candidateOps =
|
|
analysis.getCandidateOps(func);
|
|
if (!candidateOps) {
|
|
signalPassFailure();
|
|
return;
|
|
}
|
|
|
|
if (candidateOps->empty())
|
|
return;
|
|
runCount += candidateOps->size();
|
|
|
|
llvm::SmallVector<mlir::Operation *> opsToConvert;
|
|
opsToConvert.reserve(candidateOps->size());
|
|
for (auto [op, _] : *candidateOps)
|
|
opsToConvert.push_back(op);
|
|
|
|
mlir::MLIRContext &context = getContext();
|
|
mlir::RewritePatternSet patterns(&context);
|
|
mlir::GreedyRewriteConfig config;
|
|
// prevent the pattern driver form merging blocks
|
|
config.setRegionSimplificationLevel(
|
|
mlir::GreedySimplifyRegionLevel::Disabled);
|
|
|
|
auto module = func->getParentOfType<mlir::ModuleOp>();
|
|
std::optional<mlir::DataLayout> dl =
|
|
module ? fir::support::getOrSetMLIRDataLayout(
|
|
module, /*allowDefaultLayout=*/false)
|
|
: std::nullopt;
|
|
std::optional<fir::KindMapping> kindMap;
|
|
if (module)
|
|
kindMap = fir::getKindMapping(module);
|
|
|
|
patterns.insert<AllocMemConversion>(&context, *candidateOps, dl, kindMap);
|
|
if (mlir::failed(mlir::applyOpPatternsGreedily(
|
|
opsToConvert, std::move(patterns), config))) {
|
|
mlir::emitError(func->getLoc(), "error in stack arrays optimization\n");
|
|
signalPassFailure();
|
|
}
|
|
}
|