lib/Transforms/LoopUnrollAndJam.cpp - platform/external/tensorflow - Git at Google

 //===- 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.
 // =============================================================================
 //
 // 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
 // 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.
 //===----------------------------------------------------------------------===//
 #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/BuiltinOps.h"
 #include "mlir/IR/StmtVisitor.h"
 #include "mlir/Pass.h"
 #include "mlir/Transforms/LoopUtils.h"
 #include "llvm/ADT/DenseMap.h"
 #include "llvm/Support/CommandLine.h"

 using namespace mlir;

 // 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 {
 /// Loop unroll jam pass. Currently, this just unroll jams the first
 /// outer loop in an MLFunction.
 struct LoopUnrollAndJam : public FunctionPass {
   Optional<unsigned> unrollJamFactor;
   static const unsigned kDefaultUnrollJamFactor = 4;

   explicit LoopUnrollAndJam(Optional<unsigned> unrollJamFactor = None)
       : FunctionPass(&LoopUnrollAndJam::passID),
         unrollJamFactor(unrollJamFactor) {}

   PassResult runOnMLFunction(MLFunction *f) override;
   bool runOnForStmt(ForStmt *forStmt);

   static char passID;
 };
 } // end anonymous namespace

 char LoopUnrollAndJam::passID = 0;

 FunctionPass *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:
     using StmtListType = llvm::iplist<Statement>;

     // 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)
           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);

   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'.
     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);
       }
       // 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;
 }

 static PassRegistration<LoopUnrollAndJam> pass("loop-unroll-jam",
                                                "Unroll and jam loops");
	//===- 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.
	// =============================================================================
	//
	// 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
	// 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.
	//===----------------------------------------------------------------------===//
	#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/BuiltinOps.h"
	#include "mlir/IR/StmtVisitor.h"
	#include "mlir/Pass.h"
	#include "mlir/Transforms/LoopUtils.h"
	#include "llvm/ADT/DenseMap.h"
	#include "llvm/Support/CommandLine.h"

	using namespace mlir;

	// 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 {
	/// Loop unroll jam pass. Currently, this just unroll jams the first
	/// outer loop in an MLFunction.
	struct LoopUnrollAndJam : public FunctionPass {
	Optional<unsigned> unrollJamFactor;
	static const unsigned kDefaultUnrollJamFactor = 4;

	explicit LoopUnrollAndJam(Optional<unsigned> unrollJamFactor = None)
	: FunctionPass(&LoopUnrollAndJam::passID),
	unrollJamFactor(unrollJamFactor) {}

	PassResult runOnMLFunction(MLFunction *f) override;
	bool runOnForStmt(ForStmt *forStmt);

	static char passID;
	};
	} // end anonymous namespace

	char LoopUnrollAndJam::passID = 0;

	FunctionPass *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:
	using StmtListType = llvm::iplist<Statement>;

	// 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)
	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);

	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'.
	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);
	}
	// 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;
	}

	static PassRegistration<LoopUnrollAndJam> pass("loop-unroll-jam",
	"Unroll and jam loops");