llvm-project/mlir/lib/Transforms/LoopUnrollAndJam.cpp

242 lines
9.2 KiB
C++
Raw Normal View History

Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
2018-09-13 01:21:23 +08:00
//===- LoopUnrollAndJam.cpp - Code to perform loop unroll and jam ---------===//
//
// Copyright 2019 The MLIR Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// =============================================================================
//
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
2018-09-13 01:21:23 +08:00
// This file implements loop unroll and jam for MLFunctions. Unroll and jam is a
// transformation that improves locality, in particular, register reuse, while
// also improving instruction level parallelism. The example below shows what it
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
2018-09-13 01:21:23 +08:00
// does in nearly the general case. Loop unroll and jam currently works if the
// bounds of the loops inner to the loop being unroll-jammed do not depend on
// the latter.
//
// Before After unroll and jam of i by factor 2:
//
// for i, step = 2
// for i S1(i);
// S1; S2(i);
// S2; S1(i+1);
// for j S2(i+1);
// S3; for j
// S4; S3(i, j);
// S5; S4(i, j);
// S6; S3(i+1, j)
// S4(i+1, j)
// S5(i);
// S6(i);
// S5(i+1);
// S6(i+1);
//
// Note: 'if/else' blocks are not jammed. So, if there are loops inside if
// stmt's, bodies of those loops will not be jammed.
//===----------------------------------------------------------------------===//
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
2018-09-13 01:21:23 +08:00
#include "mlir/Transforms/Passes.h"
#include "mlir/Analysis/LoopAnalysis.h"
#include "mlir/IR/AffineExpr.h"
#include "mlir/IR/AffineMap.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/StandardOps.h"
#include "mlir/IR/StmtVisitor.h"
#include "mlir/Transforms/LoopUtils.h"
#include "mlir/Transforms/Pass.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/Support/CommandLine.h"
using namespace mlir;
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
2018-09-13 01:21:23 +08:00
// Loop unroll and jam factor.
static llvm::cl::opt<unsigned>
clUnrollJamFactor("unroll-jam-factor", llvm::cl::Hidden,
llvm::cl::desc("Use this unroll jam factor for all loops"
" (default 4)"));
namespace {
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
2018-09-13 01:21:23 +08:00
/// Loop unroll jam pass. Currently, this just unroll jams the first
/// outer loop in an MLFunction.
struct LoopUnrollAndJam : public MLFunctionPass {
Optional<unsigned> unrollJamFactor;
static const unsigned kDefaultUnrollJamFactor = 4;
explicit LoopUnrollAndJam(Optional<unsigned> unrollJamFactor)
: unrollJamFactor(unrollJamFactor) {}
PassResult runOnMLFunction(MLFunction *f) override;
bool runOnForStmt(ForStmt *forStmt);
};
} // end anonymous namespace
MLFunctionPass *mlir::createLoopUnrollAndJamPass(int unrollJamFactor) {
return new LoopUnrollAndJam(
unrollJamFactor == -1 ? None : Optional<unsigned>(unrollJamFactor));
}
PassResult LoopUnrollAndJam::runOnMLFunction(MLFunction *f) {
// Currently, just the outermost loop from the first loop nest is
// unroll-and-jammed by this pass. However, runOnForStmt can be called on any
// for Stmt.
if (!isa<ForStmt>(f->begin()))
return success();
auto *forStmt = cast<ForStmt>(f->begin());
runOnForStmt(forStmt);
return success();
}
/// Unroll and jam a 'for' stmt. Default unroll jam factor is
/// kDefaultUnrollJamFactor. Return false if nothing was done.
bool LoopUnrollAndJam::runOnForStmt(ForStmt *forStmt) {
// Unroll and jam by the factor that was passed if any.
if (unrollJamFactor.hasValue())
return loopUnrollJamByFactor(forStmt, unrollJamFactor.getValue());
// Otherwise, unroll jam by the command-line factor if one was specified.
if (clUnrollJamFactor.getNumOccurrences() > 0)
return loopUnrollJamByFactor(forStmt, clUnrollJamFactor);
// Unroll and jam by four otherwise.
return loopUnrollJamByFactor(forStmt, kDefaultUnrollJamFactor);
}
bool mlir::loopUnrollJamUpToFactor(ForStmt *forStmt, uint64_t unrollJamFactor) {
Optional<uint64_t> mayBeConstantTripCount = getConstantTripCount(*forStmt);
if (mayBeConstantTripCount.hasValue() &&
mayBeConstantTripCount.getValue() < unrollJamFactor)
return loopUnrollJamByFactor(forStmt, mayBeConstantTripCount.getValue());
return loopUnrollJamByFactor(forStmt, unrollJamFactor);
}
/// Unrolls and jams this loop by the specified factor.
bool mlir::loopUnrollJamByFactor(ForStmt *forStmt, uint64_t unrollJamFactor) {
// Gathers all maximal sub-blocks of statements that do not themselves include
// a for stmt (a statement could have a descendant for stmt though in its
// tree).
class JamBlockGatherer : public StmtWalker<JamBlockGatherer> {
public:
typedef llvm::iplist<Statement> StmtListType;
// Store iterators to the first and last stmt of each sub-block found.
std::vector<std::pair<StmtBlock::iterator, StmtBlock::iterator>> subBlocks;
// This is a linear time walk.
void walk(StmtListType::iterator Start, StmtListType::iterator End) {
for (auto it = Start; it != End;) {
auto subBlockStart = it;
while (it != End && !isa<ForStmt>(it))
++it;
if (it != subBlockStart)
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
2018-09-13 01:21:23 +08:00
subBlocks.push_back({subBlockStart, std::prev(it)});
// Process all for stmts that appear next.
while (it != End && isa<ForStmt>(it))
walkForStmt(cast<ForStmt>(it++));
}
}
};
assert(unrollJamFactor >= 1 && "unroll jam factor should be >= 1");
if (unrollJamFactor == 1 || forStmt->getStatements().empty())
return false;
Optional<uint64_t> mayBeConstantTripCount = getConstantTripCount(*forStmt);
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
2018-09-13 01:21:23 +08:00
if (!mayBeConstantTripCount.hasValue() &&
getLargestDivisorOfTripCount(*forStmt) % unrollJamFactor != 0)
return false;
auto *lbMap = forStmt->getLowerBoundMap();
auto *ubMap = forStmt->getUpperBoundMap();
// Loops with max/min expressions won't be unrolled here (the output can't be
// expressed as an MLFunction in the general case). However, the right way to
// do such unrolling for an MLFunction would be to specialize the loop for the
// 'hotspot' case and unroll that hotspot.
if (lbMap->getNumResults() != 1 || ubMap->getNumResults() != 1)
return false;
// Same operand list for lower and upper bound for now.
// TODO(bondhugula): handle bounds with different sets of operands.
if (!forStmt->matchingBoundOperandList())
return false;
// If the trip count is lower than the unroll jam factor, no unroll jam.
// TODO(bondhugula): option to specify cleanup loop unrolling.
if (mayBeConstantTripCount.hasValue() &&
mayBeConstantTripCount.getValue() < unrollJamFactor)
return false;
// Gather all sub-blocks to jam upon the loop being unrolled.
JamBlockGatherer jbg;
jbg.walkForStmt(forStmt);
auto &subBlocks = jbg.subBlocks;
// Generate the cleanup loop if trip count isn't a multiple of
// unrollJamFactor.
if (mayBeConstantTripCount.hasValue() &&
mayBeConstantTripCount.getValue() % unrollJamFactor != 0) {
DenseMap<const MLValue *, MLValue *> operandMap;
// Insert the cleanup loop right after 'forStmt'.
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
2018-09-13 01:21:23 +08:00
MLFuncBuilder builder(forStmt->getBlock(),
std::next(StmtBlock::iterator(forStmt)));
auto *cleanupForStmt = cast<ForStmt>(builder.clone(*forStmt, operandMap));
cleanupForStmt->setLowerBoundMap(
getCleanupLoopLowerBound(*forStmt, unrollJamFactor, &builder));
// The upper bound needs to be adjusted.
forStmt->setUpperBoundMap(
getUnrolledLoopUpperBound(*forStmt, unrollJamFactor, &builder));
// Promote the loop body up if this has turned into a single iteration loop.
promoteIfSingleIteration(cleanupForStmt);
}
// Scale the step of loop being unroll-jammed by the unroll-jam factor.
int64_t step = forStmt->getStep();
forStmt->setStep(step * unrollJamFactor);
for (auto &subBlock : subBlocks) {
// Builder to insert unroll-jammed bodies. Insert right at the end of
// sub-block.
MLFuncBuilder builder(subBlock.first->getBlock(),
std::next(subBlock.second));
// Unroll and jam (appends unrollJamFactor-1 additional copies).
for (unsigned i = 1; i < unrollJamFactor; i++) {
DenseMap<const MLValue *, MLValue *> operandMapping;
// If the induction variable is used, create a remapping to the value for
// this unrolled instance.
if (!forStmt->use_empty()) {
// iv' = iv + i, i = 1 to unrollJamFactor-1.
auto d0 = builder.getAffineDimExpr(0);
auto *bumpMap = builder.getAffineMap(1, 0, {d0 + i * step}, {});
auto *ivUnroll =
builder.create<AffineApplyOp>(forStmt->getLoc(), bumpMap, forStmt)
->getResult(0);
operandMapping[forStmt] = cast<MLValue>(ivUnroll);
}
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
2018-09-13 01:21:23 +08:00
// Clone the sub-block being unroll-jammed.
for (auto it = subBlock.first; it != std::next(subBlock.second); ++it) {
builder.clone(*it, operandMapping);
}
}
}
// Promote the loop body up if this has turned into a single iteration loop.
promoteIfSingleIteration(forStmt);
return true;
}