Mats Petersson b812932b35 [FLANG] Change loop versioning to use shift instead of divide
Despite me being convinced that the use of divide didn't produce any
divide instructions, it does in fact add more instructions than using
a plain shift operation.

This patch simply changes the divide to a shift right, with an
assert to check that the "divisor" is a power of two.

Reviewed By: kiranchandramohan, tblah

Differential Revision: https://reviews.llvm.org/D151880
2023-06-01 19:29:57 +01:00

329 lines
13 KiB
C++

//===- LoopVersioning.cpp -------------------------------------------------===//
//
// 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
//
//===----------------------------------------------------------------------===//
//===----------------------------------------------------------------------===//
/// \file
/// This pass looks for loops iterating over assumed-shape arrays, that can
/// be optimized by "guessing" that the stride is element-sized.
///
/// This is done by createing two versions of the same loop: one which assumes
/// that the elements are contiguous (stride == size of element), and one that
/// is the original generic loop.
///
/// As a side-effect of the assumed element size stride, the array is also
/// flattened to make it a 1D array - this is because the internal array
/// structure must be either 1D or have known sizes in all dimensions - and at
/// least one of the dimensions here is already unknown.
///
/// There are two distinct benefits here:
/// 1. The loop that iterates over the elements is somewhat simplified by the
/// constant stride calculation.
/// 2. Since the compiler can understand the size of the stride, it can use
/// vector instructions, where an unknown (at compile time) stride does often
/// prevent vector operations from being used.
///
/// A known drawback is that the code-size is increased, in some cases that can
/// be quite substantial - 3-4x is quite plausible (this includes that the loop
/// gets vectorized, which in itself often more than doubles the size of the
/// code, because unless the loop size is known, there will be a modulo
/// vector-size remainder to deal with.
///
/// TODO: Do we need some size limit where loops no longer get duplicated?
// Maybe some sort of cost analysis.
/// TODO: Should some loop content - for example calls to functions and
/// subroutines inhibit the versioning of the loops. Plausibly, this
/// could be part of the cost analysis above.
//===----------------------------------------------------------------------===//
#include "flang/ISO_Fortran_binding.h"
#include "flang/Optimizer/Builder/BoxValue.h"
#include "flang/Optimizer/Builder/FIRBuilder.h"
#include "flang/Optimizer/Builder/Runtime/Inquiry.h"
#include "flang/Optimizer/Dialect/FIRDialect.h"
#include "flang/Optimizer/Dialect/FIROps.h"
#include "flang/Optimizer/Dialect/FIRType.h"
#include "flang/Optimizer/Dialect/Support/FIRContext.h"
#include "flang/Optimizer/Dialect/Support/KindMapping.h"
#include "flang/Optimizer/Transforms/Passes.h"
#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
#include "mlir/IR/Matchers.h"
#include "mlir/IR/TypeUtilities.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/DialectConversion.h"
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
#include "mlir/Transforms/RegionUtils.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
#include <algorithm>
namespace fir {
#define GEN_PASS_DEF_LOOPVERSIONING
#include "flang/Optimizer/Transforms/Passes.h.inc"
} // namespace fir
#define DEBUG_TYPE "flang-loop-versioning"
namespace {
class LoopVersioningPass
: public fir::impl::LoopVersioningBase<LoopVersioningPass> {
public:
void runOnOperation() override;
};
} // namespace
/// @c replaceOuterUses - replace uses outside of @c op with result of @c
/// outerOp
static void replaceOuterUses(mlir::Operation *op, mlir::Operation *outerOp) {
const mlir::Operation *outerParent = outerOp->getParentOp();
op->replaceUsesWithIf(outerOp, [&](mlir::OpOperand &operand) {
mlir::Operation *owner = operand.getOwner();
return outerParent == owner->getParentOp();
});
}
static fir::SequenceType getAsSequenceType(mlir::Value *v) {
mlir::Type argTy = fir::unwrapPassByRefType(fir::unwrapRefType(v->getType()));
return argTy.dyn_cast<fir::SequenceType>();
}
void LoopVersioningPass::runOnOperation() {
LLVM_DEBUG(llvm::dbgs() << "=== Begin " DEBUG_TYPE " ===\n");
mlir::func::FuncOp func = getOperation();
/// @c ArgInfo
/// A structure to hold an argument, the size of the argument and dimension
/// information.
struct ArgInfo {
mlir::Value *arg;
size_t size;
unsigned rank;
fir::BoxDimsOp dims[CFI_MAX_RANK];
};
// First look for arguments with assumed shape = unknown extent in the lowest
// dimension.
LLVM_DEBUG(llvm::dbgs() << "Func-name:" << func.getSymName() << "\n");
mlir::Block::BlockArgListType args = func.getArguments();
mlir::ModuleOp module = func->getParentOfType<mlir::ModuleOp>();
fir::KindMapping kindMap = fir::getKindMapping(module);
mlir::SmallVector<ArgInfo, 4> argsOfInterest;
for (auto &arg : args) {
if (auto seqTy = getAsSequenceType(&arg)) {
unsigned rank = seqTy.getDimension();
if (rank > 0 &&
seqTy.getShape()[0] == fir::SequenceType::getUnknownExtent()) {
size_t typeSize = 0;
mlir::Type elementType = fir::unwrapSeqOrBoxedSeqType(arg.getType());
if (elementType.isa<mlir::FloatType>() ||
elementType.isa<mlir::IntegerType>())
typeSize = elementType.getIntOrFloatBitWidth() / 8;
else if (auto cty = elementType.dyn_cast<fir::ComplexType>())
typeSize = 2 * cty.getEleType(kindMap).getIntOrFloatBitWidth() / 8;
if (typeSize)
argsOfInterest.push_back({&arg, typeSize, rank, {}});
else
LLVM_DEBUG(llvm::dbgs() << "Type not supported\n");
}
}
}
if (argsOfInterest.empty())
return;
struct OpsWithArgs {
mlir::Operation *op;
mlir::SmallVector<ArgInfo, 4> argsAndDims;
};
// Now see if those arguments are used inside any loop.
mlir::SmallVector<OpsWithArgs, 4> loopsOfInterest;
func.walk([&](fir::DoLoopOp loop) {
mlir::Block &body = *loop.getBody();
mlir::SmallVector<ArgInfo, 4> argsInLoop;
body.walk([&](fir::CoordinateOp op) {
// The current operation could be inside another loop than
// the one we're currently processing. Skip it, we'll get
// to it later.
if (op->getParentOfType<fir::DoLoopOp>() != loop)
return;
const mlir::Value &operand = op->getOperand(0);
for (auto a : argsOfInterest) {
if (*a.arg == operand) {
// Only add if it's not already in the list.
if (std::find_if(argsInLoop.begin(), argsInLoop.end(), [&](auto it) {
return it.arg == a.arg;
}) == argsInLoop.end()) {
argsInLoop.push_back(a);
break;
}
}
}
});
if (!argsInLoop.empty()) {
OpsWithArgs ops = {loop, argsInLoop};
loopsOfInterest.push_back(ops);
}
});
if (loopsOfInterest.empty())
return;
// If we get here, there are loops to process.
fir::FirOpBuilder builder{module, kindMap};
mlir::Location loc = builder.getUnknownLoc();
mlir::IndexType idxTy = builder.getIndexType();
LLVM_DEBUG(llvm::dbgs() << "Module Before transformation:");
LLVM_DEBUG(module->dump());
LLVM_DEBUG(llvm::dbgs() << "loopsOfInterest: " << loopsOfInterest.size()
<< "\n");
for (auto op : loopsOfInterest) {
LLVM_DEBUG(op.op->dump());
builder.setInsertionPoint(op.op);
mlir::Value allCompares = nullptr;
// Ensure all of the arrays are unit-stride.
for (auto &arg : op.argsAndDims) {
// Fetch all the dimensions of the array, except the last dimension.
// Always fetch the first dimension, however, so set ndims = 1 if
// we have one dim
unsigned ndims = arg.rank;
for (unsigned i = 0; i < ndims; i++) {
mlir::Value dimIdx = builder.createIntegerConstant(loc, idxTy, i);
arg.dims[i] = builder.create<fir::BoxDimsOp>(loc, idxTy, idxTy, idxTy,
*arg.arg, dimIdx);
}
// We only care about lowest order dimension, here.
mlir::Value elemSize =
builder.createIntegerConstant(loc, idxTy, arg.size);
mlir::Value cmp = builder.create<mlir::arith::CmpIOp>(
loc, mlir::arith::CmpIPredicate::eq, arg.dims[0].getResult(2),
elemSize);
if (!allCompares) {
allCompares = cmp;
} else {
allCompares =
builder.create<mlir::arith::AndIOp>(loc, cmp, allCompares);
}
}
auto ifOp =
builder.create<fir::IfOp>(loc, op.op->getResultTypes(), allCompares,
/*withElse=*/true);
builder.setInsertionPointToStart(&ifOp.getThenRegion().front());
LLVM_DEBUG(llvm::dbgs() << "Creating cloned loop\n");
mlir::Operation *clonedLoop = op.op->clone();
bool changed = false;
for (auto &arg : op.argsAndDims) {
fir::SequenceType::Shape newShape;
newShape.push_back(fir::SequenceType::getUnknownExtent());
auto elementType = fir::unwrapSeqOrBoxedSeqType(arg.arg->getType());
mlir::Type arrTy = fir::SequenceType::get(newShape, elementType);
mlir::Type boxArrTy = fir::BoxType::get(arrTy);
mlir::Type refArrTy = builder.getRefType(arrTy);
auto carg = builder.create<fir::ConvertOp>(loc, boxArrTy, *arg.arg);
auto caddr = builder.create<fir::BoxAddrOp>(loc, refArrTy, carg);
auto insPt = builder.saveInsertionPoint();
// Use caddr instead of arg.
clonedLoop->walk([&](fir::CoordinateOp coop) {
// Reduce the multi-dimensioned index to a single index.
// This is required becase fir arrays do not support multiple dimensions
// with unknown dimensions at compile time.
// We then calculate the multidimensional array like this:
// arr(x, y, z) bedcomes arr(z * stride(2) + y * stride(1) + x)
// where stride is the distance between elements in the dimensions
// 0, 1 and 2 or x, y and z.
if (coop->getOperand(0) == *arg.arg &&
coop->getOperands().size() >= 2) {
builder.setInsertionPoint(coop);
mlir::Value totalIndex;
for (unsigned i = arg.rank - 1; i > 0; i--) {
// Operand(1) = array; Operand(2) = index1; Operand(3) = index2
mlir::Value curIndex =
builder.createConvert(loc, idxTy, coop->getOperand(i + 1));
// Multiply by the stride of this array. Later we'll divide by the
// element size.
mlir::Value scale =
builder.createConvert(loc, idxTy, arg.dims[i].getResult(2));
curIndex =
builder.create<mlir::arith::MulIOp>(loc, scale, curIndex);
totalIndex = (totalIndex) ? builder.create<mlir::arith::AddIOp>(
loc, curIndex, totalIndex)
: curIndex;
}
// This is the lowest dimension - which doesn't need scaling
mlir::Value finalIndex =
builder.createConvert(loc, idxTy, coop->getOperand(1));
if (totalIndex) {
assert(llvm::isPowerOf2_32(arg.size) &&
"Expected power of two here");
unsigned bits = llvm::Log2_32(arg.size);
mlir::Value elemShift =
builder.createIntegerConstant(loc, idxTy, bits);
totalIndex = builder.create<mlir::arith::AddIOp>(
loc,
builder.create<mlir::arith::ShRSIOp>(loc, totalIndex,
elemShift),
finalIndex);
} else {
totalIndex = finalIndex;
}
auto newOp = builder.create<fir::CoordinateOp>(
loc, builder.getRefType(elementType), caddr,
mlir::ValueRange{totalIndex});
LLVM_DEBUG(newOp->dump());
coop->getResult(0).replaceAllUsesWith(newOp->getResult(0));
coop->erase();
changed = true;
}
});
builder.restoreInsertionPoint(insPt);
}
assert(changed && "Expected operations to have changed");
builder.insert(clonedLoop);
// Forward the result(s), if any, from the loop operation to the
//
mlir::ResultRange results = clonedLoop->getResults();
bool hasResults = (results.size() > 0);
if (hasResults)
builder.create<fir::ResultOp>(loc, results);
// Add the original loop in the else-side of the if operation.
builder.setInsertionPointToStart(&ifOp.getElseRegion().front());
replaceOuterUses(op.op, ifOp);
op.op->remove();
builder.insert(op.op);
// Rely on "cloned loop has results, so original loop also has results".
if (hasResults) {
builder.create<fir::ResultOp>(loc, op.op->getResults());
} else {
// Use an assert to check this.
assert(op.op->getResults().size() == 0 &&
"Weird, the cloned loop doesn't have results, but the original "
"does?");
}
}
LLVM_DEBUG(llvm::dbgs() << "After transform:\n");
LLVM_DEBUG(module->dump());
LLVM_DEBUG(llvm::dbgs() << "=== End " DEBUG_TYPE " ===\n");
}
std::unique_ptr<mlir::Pass> fir::createLoopVersioningPass() {
return std::make_unique<LoopVersioningPass>();
}