27c201aa1d
This allows conversion of a ParallelLoop from N induction variables to some nuber of induction variables less than N. The first intended use of this is for the GPUDialect to convert ParallelLoops to iterate over 3 dimensions so they can be launched as GPU Kernels. To implement this: - Normalize each iteration space of the ParallelLoop - Use the same induction variable in a new ParallelLoop for multiple original iterations. - Split the new induction variable back into the original set of values inside the body of the ParallelLoop. Subscribers: mgorny, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, llvm-commits Tags: #llvm Differential Revision: https://reviews.llvm.org/D76363
70 lines
2.5 KiB
C++
70 lines
2.5 KiB
C++
//===- ParallelLoopCollapsing.cpp - Pass collapsing parallel loop indices -===//
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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 "mlir/Dialect/LoopOps/LoopOps.h"
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#include "mlir/Dialect/StandardOps/IR/Ops.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Transforms/LoopUtils.h"
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#include "mlir/Transforms/Passes.h"
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#include "mlir/Transforms/RegionUtils.h"
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#include "llvm/Support/CommandLine.h"
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#include "llvm/Support/Debug.h"
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#define PASS_NAME "parallel-loop-collapsing"
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#define DEBUG_TYPE PASS_NAME
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using namespace mlir;
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namespace {
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struct ParallelLoopCollapsing : public OperationPass<ParallelLoopCollapsing> {
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ParallelLoopCollapsing() = default;
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ParallelLoopCollapsing(const ParallelLoopCollapsing &) {}
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void runOnOperation() override {
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Operation *module = getOperation();
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module->walk([&](loop::ParallelOp op) {
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// The common case for GPU dialect will be simplifying the ParallelOp to 3
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// arguments, so we do that here to simplify things.
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llvm::SmallVector<std::vector<unsigned>, 3> combinedLoops;
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if (clCollapsedIndices0.size())
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combinedLoops.push_back(clCollapsedIndices0);
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if (clCollapsedIndices1.size())
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combinedLoops.push_back(clCollapsedIndices1);
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if (clCollapsedIndices2.size())
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combinedLoops.push_back(clCollapsedIndices2);
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collapsePLoops(op, combinedLoops);
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});
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}
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ListOption<unsigned> clCollapsedIndices0{
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*this, "collapsed-indices-0",
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llvm::cl::desc("Which loop indices to combine 0th loop index"),
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llvm::cl::MiscFlags::CommaSeparated};
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ListOption<unsigned> clCollapsedIndices1{
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*this, "collapsed-indices-1",
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llvm::cl::desc(
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"Which loop indices to combine into the position 1 loop index"),
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llvm::cl::MiscFlags::CommaSeparated};
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ListOption<unsigned> clCollapsedIndices2{
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*this, "collapsed-indices-2",
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llvm::cl::desc(
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"Which loop indices to combine into the position 2 loop index"),
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llvm::cl::MiscFlags::CommaSeparated};
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};
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} // namespace
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std::unique_ptr<Pass> mlir::createParallelLoopCollapsingPass() {
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return std::make_unique<ParallelLoopCollapsing>();
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}
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static PassRegistration<ParallelLoopCollapsing>
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reg(PASS_NAME, "collapse parallel loops to use less induction variables.");
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