This patch makes more than 2D arrays work, with a fix for the way that loop index is calculated. Removing the restriction of number of dimensions. This also changes the way that the actual index is calculated, such that the stride is used rather than the extent of the previous dimension. Some tests failed without fixing this - this was likely a latent bug in the 2D version too, but found in a test using 3D arrays, so wouldn't have been found with 2D only. This introduces a division on the index calculation - however it should be a nice and constant value allowing a shift to be used to actually divide - or otherwise removed by using other methods to calculate the result. In analysing code generated with optimisation at -O3, there are no divides produced. Some minor refactoring to avoid repeatedly asking for the "rank" of the array being worked on. This improves some of the SPEC-2017 ROMS code, in the same way as the limited 2D array improvements - less overhead spent calculating array indices in the inner-most loop and better use of vector-instructions. Reviewed By: kiranchandramohan Differential Revision: https://reviews.llvm.org/D151140
325 lines
13 KiB
C++
325 lines
13 KiB
C++
//===- LoopVersioning.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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//===----------------------------------------------------------------------===//
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/// \file
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/// This pass looks for loops iterating over assumed-shape arrays, that can
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/// be optimized by "guessing" that the stride is element-sized.
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///
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/// This is done by createing two versions of the same loop: one which assumes
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/// that the elements are contiguous (stride == size of element), and one that
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/// is the original generic loop.
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///
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/// As a side-effect of the assumed element size stride, the array is also
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/// flattened to make it a 1D array - this is because the internal array
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/// structure must be either 1D or have known sizes in all dimensions - and at
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/// least one of the dimensions here is already unknown.
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///
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/// There are two distinct benefits here:
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/// 1. The loop that iterates over the elements is somewhat simplified by the
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/// constant stride calculation.
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/// 2. Since the compiler can understand the size of the stride, it can use
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/// vector instructions, where an unknown (at compile time) stride does often
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/// prevent vector operations from being used.
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///
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/// A known drawback is that the code-size is increased, in some cases that can
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/// be quite substantial - 3-4x is quite plausible (this includes that the loop
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/// gets vectorized, which in itself often more than doubles the size of the
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/// code, because unless the loop size is known, there will be a modulo
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/// vector-size remainder to deal with.
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///
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/// TODO: Do we need some size limit where loops no longer get duplicated?
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// Maybe some sort of cost analysis.
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/// TODO: Should some loop content - for example calls to functions and
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/// subroutines inhibit the versioning of the loops. Plausibly, this
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/// could be part of the cost analysis above.
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//===----------------------------------------------------------------------===//
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#include "flang/ISO_Fortran_binding.h"
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#include "flang/Optimizer/Builder/BoxValue.h"
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#include "flang/Optimizer/Builder/FIRBuilder.h"
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#include "flang/Optimizer/Builder/Runtime/Inquiry.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/Dialect/Support/KindMapping.h"
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#include "flang/Optimizer/Transforms/Passes.h"
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#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
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#include "mlir/IR/Matchers.h"
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#include "mlir/IR/TypeUtilities.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Transforms/DialectConversion.h"
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#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
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#include "mlir/Transforms/RegionUtils.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 <algorithm>
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namespace fir {
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#define GEN_PASS_DEF_LOOPVERSIONING
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#include "flang/Optimizer/Transforms/Passes.h.inc"
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} // namespace fir
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#define DEBUG_TYPE "flang-loop-versioning"
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namespace {
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class LoopVersioningPass
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: public fir::impl::LoopVersioningBase<LoopVersioningPass> {
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public:
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void runOnOperation() override;
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};
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} // namespace
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/// @c replaceOuterUses - replace uses outside of @c op with result of @c
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/// outerOp
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static void replaceOuterUses(mlir::Operation *op, mlir::Operation *outerOp) {
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const mlir::Operation *outerParent = outerOp->getParentOp();
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op->replaceUsesWithIf(outerOp, [&](mlir::OpOperand &operand) {
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mlir::Operation *owner = operand.getOwner();
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return outerParent == owner->getParentOp();
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});
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}
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static fir::SequenceType getAsSequenceType(mlir::Value *v) {
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mlir::Type argTy = fir::unwrapPassByRefType(fir::unwrapRefType(v->getType()));
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return argTy.dyn_cast<fir::SequenceType>();
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}
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void LoopVersioningPass::runOnOperation() {
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LLVM_DEBUG(llvm::dbgs() << "=== Begin " DEBUG_TYPE " ===\n");
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mlir::func::FuncOp func = getOperation();
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/// @c ArgInfo
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/// A structure to hold an argument, the size of the argument and dimension
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/// information.
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struct ArgInfo {
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mlir::Value *arg;
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size_t size;
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unsigned rank;
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fir::BoxDimsOp dims[CFI_MAX_RANK];
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};
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// First look for arguments with assumed shape = unknown extent in the lowest
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// dimension.
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LLVM_DEBUG(llvm::dbgs() << "Func-name:" << func.getSymName() << "\n");
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mlir::Block::BlockArgListType args = func.getArguments();
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mlir::ModuleOp module = func->getParentOfType<mlir::ModuleOp>();
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fir::KindMapping kindMap = fir::getKindMapping(module);
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mlir::SmallVector<ArgInfo, 4> argsOfInterest;
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for (auto &arg : args) {
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if (auto seqTy = getAsSequenceType(&arg)) {
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unsigned rank = seqTy.getDimension();
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if (rank > 0 &&
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seqTy.getShape()[0] == fir::SequenceType::getUnknownExtent()) {
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size_t typeSize = 0;
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mlir::Type elementType = fir::unwrapSeqOrBoxedSeqType(arg.getType());
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if (elementType.isa<mlir::FloatType>() ||
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elementType.isa<mlir::IntegerType>())
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typeSize = elementType.getIntOrFloatBitWidth() / 8;
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else if (auto cty = elementType.dyn_cast<fir::ComplexType>())
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typeSize = 2 * cty.getEleType(kindMap).getIntOrFloatBitWidth() / 8;
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if (typeSize)
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argsOfInterest.push_back({&arg, typeSize, rank, {}});
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else
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LLVM_DEBUG(llvm::dbgs() << "Type not supported\n");
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}
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}
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}
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if (argsOfInterest.empty())
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return;
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struct OpsWithArgs {
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mlir::Operation *op;
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mlir::SmallVector<ArgInfo, 4> argsAndDims;
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};
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// Now see if those arguments are used inside any loop.
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mlir::SmallVector<OpsWithArgs, 4> loopsOfInterest;
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func.walk([&](fir::DoLoopOp loop) {
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mlir::Block &body = *loop.getBody();
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mlir::SmallVector<ArgInfo, 4> argsInLoop;
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body.walk([&](fir::CoordinateOp op) {
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// The current operation could be inside another loop than
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// the one we're currently processing. Skip it, we'll get
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// to it later.
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if (op->getParentOfType<fir::DoLoopOp>() != loop)
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return;
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const mlir::Value &operand = op->getOperand(0);
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for (auto a : argsOfInterest) {
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if (*a.arg == operand) {
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// Only add if it's not already in the list.
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if (std::find_if(argsInLoop.begin(), argsInLoop.end(), [&](auto it) {
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return it.arg == a.arg;
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}) == argsInLoop.end()) {
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argsInLoop.push_back(a);
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break;
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}
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}
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}
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});
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if (!argsInLoop.empty()) {
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OpsWithArgs ops = {loop, argsInLoop};
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loopsOfInterest.push_back(ops);
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}
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});
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if (loopsOfInterest.empty())
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return;
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// If we get here, there are loops to process.
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fir::FirOpBuilder builder{module, kindMap};
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mlir::Location loc = builder.getUnknownLoc();
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mlir::IndexType idxTy = builder.getIndexType();
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LLVM_DEBUG(llvm::dbgs() << "Module Before transformation:");
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LLVM_DEBUG(module->dump());
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LLVM_DEBUG(llvm::dbgs() << "loopsOfInterest: " << loopsOfInterest.size()
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<< "\n");
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for (auto op : loopsOfInterest) {
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LLVM_DEBUG(op.op->dump());
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builder.setInsertionPoint(op.op);
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mlir::Value allCompares = nullptr;
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// Ensure all of the arrays are unit-stride.
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for (auto &arg : op.argsAndDims) {
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// Fetch all the dimensions of the array, except the last dimension.
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// Always fetch the first dimension, however, so set ndims = 1 if
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// we have one dim
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unsigned ndims = arg.rank;
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for (unsigned i = 0; i < ndims; i++) {
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mlir::Value dimIdx = builder.createIntegerConstant(loc, idxTy, i);
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arg.dims[i] = builder.create<fir::BoxDimsOp>(loc, idxTy, idxTy, idxTy,
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*arg.arg, dimIdx);
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}
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// We only care about lowest order dimension, here.
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mlir::Value elemSize =
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builder.createIntegerConstant(loc, idxTy, arg.size);
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mlir::Value cmp = builder.create<mlir::arith::CmpIOp>(
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loc, mlir::arith::CmpIPredicate::eq, arg.dims[0].getResult(2),
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elemSize);
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if (!allCompares) {
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allCompares = cmp;
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} else {
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allCompares =
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builder.create<mlir::arith::AndIOp>(loc, cmp, allCompares);
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}
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}
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auto ifOp =
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builder.create<fir::IfOp>(loc, op.op->getResultTypes(), allCompares,
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/*withElse=*/true);
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builder.setInsertionPointToStart(&ifOp.getThenRegion().front());
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LLVM_DEBUG(llvm::dbgs() << "Creating cloned loop\n");
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mlir::Operation *clonedLoop = op.op->clone();
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bool changed = false;
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for (auto &arg : op.argsAndDims) {
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fir::SequenceType::Shape newShape;
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newShape.push_back(fir::SequenceType::getUnknownExtent());
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auto elementType = fir::unwrapSeqOrBoxedSeqType(arg.arg->getType());
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mlir::Type arrTy = fir::SequenceType::get(newShape, elementType);
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mlir::Type boxArrTy = fir::BoxType::get(arrTy);
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mlir::Type refArrTy = builder.getRefType(arrTy);
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auto carg = builder.create<fir::ConvertOp>(loc, boxArrTy, *arg.arg);
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auto caddr = builder.create<fir::BoxAddrOp>(loc, refArrTy, carg);
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auto insPt = builder.saveInsertionPoint();
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// Use caddr instead of arg.
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clonedLoop->walk([&](fir::CoordinateOp coop) {
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// Reduce the multi-dimensioned index to a single index.
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// This is required becase fir arrays do not support multiple dimensions
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// with unknown dimensions at compile time.
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// We then calculate the multidimensional array like this:
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// arr(x, y, z) bedcomes arr(z * stride(2) + y * stride(1) + x)
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// where stride is the distance between elements in the dimensions
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// 0, 1 and 2 or x, y and z.
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if (coop->getOperand(0) == *arg.arg &&
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coop->getOperands().size() >= 2) {
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builder.setInsertionPoint(coop);
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mlir::Value totalIndex;
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for (unsigned i = arg.rank - 1; i > 0; i--) {
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// Operand(1) = array; Operand(2) = index1; Operand(3) = index2
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mlir::Value curIndex =
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builder.createConvert(loc, idxTy, coop->getOperand(i + 1));
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// Multiply by the stride of this array. Later we'll divide by the
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// element size.
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mlir::Value scale =
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builder.createConvert(loc, idxTy, arg.dims[i].getResult(2));
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curIndex =
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builder.create<mlir::arith::MulIOp>(loc, scale, curIndex);
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totalIndex = (totalIndex) ? builder.create<mlir::arith::AddIOp>(
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loc, curIndex, totalIndex)
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: curIndex;
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}
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mlir::Value elemSize =
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builder.createIntegerConstant(loc, idxTy, arg.size);
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// This is the lowest dimension - which doesn't need scaling
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mlir::Value finalIndex =
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builder.createConvert(loc, idxTy, coop->getOperand(1));
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if (totalIndex) {
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totalIndex = builder.create<mlir::arith::AddIOp>(
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loc,
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builder.create<mlir::arith::DivSIOp>(loc, totalIndex, elemSize),
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finalIndex);
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} else {
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totalIndex = finalIndex;
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}
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auto newOp = builder.create<fir::CoordinateOp>(
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loc, builder.getRefType(elementType), caddr,
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mlir::ValueRange{totalIndex});
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LLVM_DEBUG(newOp->dump());
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coop->getResult(0).replaceAllUsesWith(newOp->getResult(0));
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coop->erase();
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changed = true;
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}
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});
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builder.restoreInsertionPoint(insPt);
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}
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assert(changed && "Expected operations to have changed");
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builder.insert(clonedLoop);
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// Forward the result(s), if any, from the loop operation to the
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//
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mlir::ResultRange results = clonedLoop->getResults();
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bool hasResults = (results.size() > 0);
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if (hasResults)
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builder.create<fir::ResultOp>(loc, results);
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// Add the original loop in the else-side of the if operation.
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builder.setInsertionPointToStart(&ifOp.getElseRegion().front());
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replaceOuterUses(op.op, ifOp);
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op.op->remove();
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builder.insert(op.op);
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// Rely on "cloned loop has results, so original loop also has results".
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if (hasResults) {
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builder.create<fir::ResultOp>(loc, op.op->getResults());
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} else {
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// Use an assert to check this.
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assert(op.op->getResults().size() == 0 &&
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"Weird, the cloned loop doesn't have results, but the original "
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"does?");
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}
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}
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LLVM_DEBUG(llvm::dbgs() << "After transform:\n");
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LLVM_DEBUG(module->dump());
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LLVM_DEBUG(llvm::dbgs() << "=== End " DEBUG_TYPE " ===\n");
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}
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std::unique_ptr<mlir::Pass> fir::createLoopVersioningPass() {
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return std::make_unique<LoopVersioningPass>();
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}
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