Files
clang-p2996/mlir/lib/Dialect/Affine/Transforms/PipelineDataTransfer.cpp
Tres Popp 5550c82189 [mlir] Move casting calls from methods to function calls
The MLIR classes Type/Attribute/Operation/Op/Value support
cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast
functionality in addition to defining methods with the same name.
This change begins the migration of uses of the method to the
corresponding function call as has been decided as more consistent.

Note that there still exist classes that only define methods directly,
such as AffineExpr, and this does not include work currently to support
a functional cast/isa call.

Caveats include:
- This clang-tidy script probably has more problems.
- This only touches C++ code, so nothing that is being generated.

Context:
- https://mlir.llvm.org/deprecation/ at "Use the free function variants
  for dyn_cast/cast/isa/…"
- Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443

Implementation:
This first patch was created with the following steps. The intention is
to only do automated changes at first, so I waste less time if it's
reverted, and so the first mass change is more clear as an example to
other teams that will need to follow similar steps.

Steps are described per line, as comments are removed by git:
0. Retrieve the change from the following to build clang-tidy with an
   additional check:
   https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check
1. Build clang-tidy
2. Run clang-tidy over your entire codebase while disabling all checks
   and enabling the one relevant one. Run on all header files also.
3. Delete .inc files that were also modified, so the next build rebuilds
   them to a pure state.
4. Some changes have been deleted for the following reasons:
   - Some files had a variable also named cast
   - Some files had not included a header file that defines the cast
     functions
   - Some files are definitions of the classes that have the casting
     methods, so the code still refers to the method instead of the
     function without adding a prefix or removing the method declaration
     at the same time.

```
ninja -C $BUILD_DIR clang-tidy

run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\
               -header-filter=mlir/ mlir/* -fix

rm -rf $BUILD_DIR/tools/mlir/**/*.inc

git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\
            mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\
            mlir/lib/**/IR/\
            mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\
            mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\
            mlir/test/lib/Dialect/Test/TestTypes.cpp\
            mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\
            mlir/test/lib/Dialect/Test/TestAttributes.cpp\
            mlir/unittests/TableGen/EnumsGenTest.cpp\
            mlir/test/python/lib/PythonTestCAPI.cpp\
            mlir/include/mlir/IR/
```

Differential Revision: https://reviews.llvm.org/D150123
2023-05-12 11:21:25 +02:00

381 lines
14 KiB
C++

//===- PipelineDataTransfer.cpp --- Pass for pipelining data movement ---*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// This file implements a pass to pipeline data transfers.
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Affine/Passes.h"
#include "mlir/Dialect/Affine/Analysis/AffineAnalysis.h"
#include "mlir/Dialect/Affine/Analysis/LoopAnalysis.h"
#include "mlir/Dialect/Affine/Analysis/Utils.h"
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/Affine/LoopUtils.h"
#include "mlir/Dialect/Affine/Utils.h"
#include "mlir/Dialect/Arith/Utils/Utils.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/IR/Builders.h"
#include "mlir/Transforms/Passes.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/Support/Debug.h"
namespace mlir {
namespace affine {
#define GEN_PASS_DEF_AFFINEPIPELINEDATATRANSFER
#include "mlir/Dialect/Affine/Passes.h.inc"
} // namespace affine
} // namespace mlir
#define DEBUG_TYPE "affine-pipeline-data-transfer"
using namespace mlir;
using namespace mlir::affine;
namespace {
struct PipelineDataTransfer
: public affine::impl::AffinePipelineDataTransferBase<
PipelineDataTransfer> {
void runOnOperation() override;
void runOnAffineForOp(AffineForOp forOp);
std::vector<AffineForOp> forOps;
};
} // namespace
/// Creates a pass to pipeline explicit movement of data across levels of the
/// memory hierarchy.
std::unique_ptr<OperationPass<func::FuncOp>>
mlir::affine::createPipelineDataTransferPass() {
return std::make_unique<PipelineDataTransfer>();
}
// Returns the position of the tag memref operand given a DMA operation.
// Temporary utility: will be replaced when DmaStart/DmaFinish abstract op's are
// added. TODO
static unsigned getTagMemRefPos(Operation &dmaOp) {
assert((isa<AffineDmaStartOp, AffineDmaWaitOp>(dmaOp)));
if (auto dmaStartOp = dyn_cast<AffineDmaStartOp>(dmaOp)) {
return dmaStartOp.getTagMemRefOperandIndex();
}
// First operand for a dma finish operation.
return 0;
}
/// Doubles the buffer of the supplied memref on the specified 'affine.for'
/// operation by adding a leading dimension of size two to the memref.
/// Replaces all uses of the old memref by the new one while indexing the newly
/// added dimension by the loop IV of the specified 'affine.for' operation
/// modulo 2. Returns false if such a replacement cannot be performed.
static bool doubleBuffer(Value oldMemRef, AffineForOp forOp) {
auto *forBody = forOp.getBody();
OpBuilder bInner(forBody, forBody->begin());
// Doubles the shape with a leading dimension extent of 2.
auto doubleShape = [&](MemRefType oldMemRefType) -> MemRefType {
// Add the leading dimension in the shape for the double buffer.
ArrayRef<int64_t> oldShape = oldMemRefType.getShape();
SmallVector<int64_t, 4> newShape(1 + oldMemRefType.getRank());
newShape[0] = 2;
std::copy(oldShape.begin(), oldShape.end(), newShape.begin() + 1);
return MemRefType::Builder(oldMemRefType).setShape(newShape).setLayout({});
};
auto oldMemRefType = cast<MemRefType>(oldMemRef.getType());
auto newMemRefType = doubleShape(oldMemRefType);
// The double buffer is allocated right before 'forOp'.
OpBuilder bOuter(forOp);
// Put together alloc operands for any dynamic dimensions of the memref.
SmallVector<Value, 4> allocOperands;
for (const auto &dim : llvm::enumerate(oldMemRefType.getShape())) {
if (dim.value() == ShapedType::kDynamic)
allocOperands.push_back(bOuter.createOrFold<memref::DimOp>(
forOp.getLoc(), oldMemRef, dim.index()));
}
// Create and place the alloc right before the 'affine.for' operation.
Value newMemRef = bOuter.create<memref::AllocOp>(
forOp.getLoc(), newMemRefType, allocOperands);
// Create 'iv mod 2' value to index the leading dimension.
auto d0 = bInner.getAffineDimExpr(0);
int64_t step = forOp.getStep();
auto modTwoMap =
AffineMap::get(/*dimCount=*/1, /*symbolCount=*/0, d0.floorDiv(step) % 2);
auto ivModTwoOp = bInner.create<AffineApplyOp>(forOp.getLoc(), modTwoMap,
forOp.getInductionVar());
// replaceAllMemRefUsesWith will succeed unless the forOp body has
// non-dereferencing uses of the memref (dealloc's are fine though).
if (failed(replaceAllMemRefUsesWith(
oldMemRef, newMemRef,
/*extraIndices=*/{ivModTwoOp},
/*indexRemap=*/AffineMap(),
/*extraOperands=*/{},
/*symbolOperands=*/{},
/*domOpFilter=*/&*forOp.getBody()->begin()))) {
LLVM_DEBUG(
forOp.emitError("memref replacement for double buffering failed"));
ivModTwoOp.erase();
return false;
}
// Insert the dealloc op right after the for loop.
bOuter.setInsertionPointAfter(forOp);
bOuter.create<memref::DeallocOp>(forOp.getLoc(), newMemRef);
return true;
}
/// Returns success if the IR is in a valid state.
void PipelineDataTransfer::runOnOperation() {
// Do a post order walk so that inner loop DMAs are processed first. This is
// necessary since 'affine.for' operations nested within would otherwise
// become invalid (erased) when the outer loop is pipelined (the pipelined one
// gets deleted and replaced by a prologue, a new steady-state loop and an
// epilogue).
forOps.clear();
getOperation().walk([&](AffineForOp forOp) { forOps.push_back(forOp); });
for (auto forOp : forOps)
runOnAffineForOp(forOp);
}
// Check if tags of the dma start op and dma wait op match.
static bool checkTagMatch(AffineDmaStartOp startOp, AffineDmaWaitOp waitOp) {
if (startOp.getTagMemRef() != waitOp.getTagMemRef())
return false;
auto startIndices = startOp.getTagIndices();
auto waitIndices = waitOp.getTagIndices();
// Both of these have the same number of indices since they correspond to the
// same tag memref.
for (auto it = startIndices.begin(), wIt = waitIndices.begin(),
e = startIndices.end();
it != e; ++it, ++wIt) {
// Keep it simple for now, just checking if indices match.
// TODO: this would in general need to check if there is no
// intervening write writing to the same tag location, i.e., memory last
// write/data flow analysis. This is however sufficient/powerful enough for
// now since the DMA generation pass or the input for it will always have
// start/wait with matching tags (same SSA operand indices).
if (*it != *wIt)
return false;
}
return true;
}
// Identify matching DMA start/finish operations to overlap computation with.
static void findMatchingStartFinishInsts(
AffineForOp forOp,
SmallVectorImpl<std::pair<Operation *, Operation *>> &startWaitPairs) {
// Collect outgoing DMA operations - needed to check for dependences below.
SmallVector<AffineDmaStartOp, 4> outgoingDmaOps;
for (auto &op : *forOp.getBody()) {
auto dmaStartOp = dyn_cast<AffineDmaStartOp>(op);
if (dmaStartOp && dmaStartOp.isSrcMemorySpaceFaster())
outgoingDmaOps.push_back(dmaStartOp);
}
SmallVector<Operation *, 4> dmaStartInsts, dmaFinishInsts;
for (auto &op : *forOp.getBody()) {
// Collect DMA finish operations.
if (isa<AffineDmaWaitOp>(op)) {
dmaFinishInsts.push_back(&op);
continue;
}
auto dmaStartOp = dyn_cast<AffineDmaStartOp>(op);
if (!dmaStartOp)
continue;
// Only DMAs incoming into higher memory spaces are pipelined for now.
// TODO: handle outgoing DMA pipelining.
if (!dmaStartOp.isDestMemorySpaceFaster())
continue;
// Check for dependence with outgoing DMAs. Doing this conservatively.
// TODO: use the dependence analysis to check for
// dependences between an incoming and outgoing DMA in the same iteration.
auto *it = outgoingDmaOps.begin();
for (; it != outgoingDmaOps.end(); ++it) {
if (it->getDstMemRef() == dmaStartOp.getSrcMemRef())
break;
}
if (it != outgoingDmaOps.end())
continue;
// We only double buffer if the buffer is not live out of loop.
auto memref = dmaStartOp.getOperand(dmaStartOp.getFasterMemPos());
bool escapingUses = false;
for (auto *user : memref.getUsers()) {
// We can double buffer regardless of dealloc's outside the loop.
if (isa<memref::DeallocOp>(user))
continue;
if (!forOp.getBody()->findAncestorOpInBlock(*user)) {
LLVM_DEBUG(llvm::dbgs()
<< "can't pipeline: buffer is live out of loop\n";);
escapingUses = true;
break;
}
}
if (!escapingUses)
dmaStartInsts.push_back(&op);
}
// For each start operation, we look for a matching finish operation.
for (auto *dmaStartOp : dmaStartInsts) {
for (auto *dmaFinishOp : dmaFinishInsts) {
if (checkTagMatch(cast<AffineDmaStartOp>(dmaStartOp),
cast<AffineDmaWaitOp>(dmaFinishOp))) {
startWaitPairs.push_back({dmaStartOp, dmaFinishOp});
break;
}
}
}
}
/// Overlap DMA transfers with computation in this loop. If successful,
/// 'forOp' is deleted, and a prologue, a new pipelined loop, and epilogue are
/// inserted right before where it was.
void PipelineDataTransfer::runOnAffineForOp(AffineForOp forOp) {
auto mayBeConstTripCount = getConstantTripCount(forOp);
if (!mayBeConstTripCount) {
LLVM_DEBUG(forOp.emitRemark("won't pipeline due to unknown trip count"));
return;
}
SmallVector<std::pair<Operation *, Operation *>, 4> startWaitPairs;
findMatchingStartFinishInsts(forOp, startWaitPairs);
if (startWaitPairs.empty()) {
LLVM_DEBUG(forOp.emitRemark("No dma start/finish pairs\n"));
return;
}
// Double the buffers for the higher memory space memref's.
// Identify memref's to replace by scanning through all DMA start
// operations. A DMA start operation has two memref's - the one from the
// higher level of memory hierarchy is the one to double buffer.
// TODO: check whether double-buffering is even necessary.
// TODO: make this work with different layouts: assuming here that
// the dimension we are adding here for the double buffering is the outermost
// dimension.
for (auto &pair : startWaitPairs) {
auto *dmaStartOp = pair.first;
Value oldMemRef = dmaStartOp->getOperand(
cast<AffineDmaStartOp>(dmaStartOp).getFasterMemPos());
if (!doubleBuffer(oldMemRef, forOp)) {
// Normally, double buffering should not fail because we already checked
// that there are no uses outside.
LLVM_DEBUG(llvm::dbgs()
<< "double buffering failed for" << dmaStartOp << "\n";);
// IR still valid and semantically correct.
return;
}
// If the old memref has no more uses, remove its 'dead' alloc if it was
// alloc'ed. (note: DMA buffers are rarely function live-in; but a 'dim'
// operation could have been used on it if it was dynamically shaped in
// order to create the double buffer above.)
// '-canonicalize' does this in a more general way, but we'll anyway do the
// simple/common case so that the output / test cases looks clear.
if (auto *allocOp = oldMemRef.getDefiningOp()) {
if (oldMemRef.use_empty()) {
allocOp->erase();
} else if (oldMemRef.hasOneUse()) {
if (auto dealloc =
dyn_cast<memref::DeallocOp>(*oldMemRef.user_begin())) {
dealloc.erase();
allocOp->erase();
}
}
}
}
// Double the buffers for tag memrefs.
for (auto &pair : startWaitPairs) {
auto *dmaFinishOp = pair.second;
Value oldTagMemRef = dmaFinishOp->getOperand(getTagMemRefPos(*dmaFinishOp));
if (!doubleBuffer(oldTagMemRef, forOp)) {
LLVM_DEBUG(llvm::dbgs() << "tag double buffering failed\n";);
return;
}
// If the old tag has no uses or a single dealloc use, remove it.
// (canonicalization handles more complex cases).
if (auto *tagAllocOp = oldTagMemRef.getDefiningOp()) {
if (oldTagMemRef.use_empty()) {
tagAllocOp->erase();
} else if (oldTagMemRef.hasOneUse()) {
if (auto dealloc =
dyn_cast<memref::DeallocOp>(*oldTagMemRef.user_begin())) {
dealloc.erase();
tagAllocOp->erase();
}
}
}
}
// Double buffering would have invalidated all the old DMA start/wait insts.
startWaitPairs.clear();
findMatchingStartFinishInsts(forOp, startWaitPairs);
// Store shift for operation for later lookup for AffineApplyOp's.
DenseMap<Operation *, unsigned> instShiftMap;
for (auto &pair : startWaitPairs) {
auto *dmaStartOp = pair.first;
assert(isa<AffineDmaStartOp>(dmaStartOp));
instShiftMap[dmaStartOp] = 0;
// Set shifts for DMA start op's affine operand computation slices to 0.
SmallVector<AffineApplyOp, 4> sliceOps;
affine::createAffineComputationSlice(dmaStartOp, &sliceOps);
if (!sliceOps.empty()) {
for (auto sliceOp : sliceOps) {
instShiftMap[sliceOp.getOperation()] = 0;
}
} else {
// If a slice wasn't created, the reachable affine.apply op's from its
// operands are the ones that go with it.
SmallVector<Operation *, 4> affineApplyInsts;
SmallVector<Value, 4> operands(dmaStartOp->getOperands());
getReachableAffineApplyOps(operands, affineApplyInsts);
for (auto *op : affineApplyInsts) {
instShiftMap[op] = 0;
}
}
}
// Everything else (including compute ops and dma finish) are shifted by one.
for (auto &op : forOp.getBody()->without_terminator())
if (!instShiftMap.contains(&op))
instShiftMap[&op] = 1;
// Get shifts stored in map.
SmallVector<uint64_t, 8> shifts(forOp.getBody()->getOperations().size());
unsigned s = 0;
for (auto &op : forOp.getBody()->without_terminator()) {
assert(instShiftMap.contains(&op));
shifts[s++] = instShiftMap[&op];
// Tagging operations with shifts for debugging purposes.
LLVM_DEBUG({
OpBuilder b(&op);
op.setAttr("shift", b.getI64IntegerAttr(shifts[s - 1]));
});
}
if (!isOpwiseShiftValid(forOp, shifts)) {
// Violates dependences.
LLVM_DEBUG(llvm::dbgs() << "Shifts invalid - unexpected\n";);
return;
}
if (failed(affineForOpBodySkew(forOp, shifts))) {
LLVM_DEBUG(llvm::dbgs() << "op body skewing failed - unexpected\n";);
return;
}
}