27 #include "llvm/ADT/DenseMap.h"
30 #define GEN_PASS_DEF_SCFFORLOOPPEELING
31 #define GEN_PASS_DEF_SCFFORLOOPSPECIALIZATION
32 #define GEN_PASS_DEF_SCFPARALLELLOOPSPECIALIZATION
33 #include "mlir/Dialect/SCF/Transforms/Passes.h.inc"
39 using scf::ParallelOp;
47 constantIndices.reserve(op.getUpperBound().size());
48 for (
auto bound : op.getUpperBound()) {
49 auto minOp = bound.getDefiningOp<AffineMinOp>();
53 for (
AffineExpr expr : minOp.getMap().getResults()) {
59 constantIndices.push_back(minConstant);
65 for (
auto bound : llvm::zip(op.getUpperBound(), constantIndices)) {
67 b.
create<arith::ConstantIndexOp>(op.getLoc(), std::get<1>(bound));
68 Value cmp = b.
create<arith::CmpIOp>(op.getLoc(), arith::CmpIPredicate::eq,
69 std::get<0>(bound), constant);
70 cond = cond ? b.
create<arith::AndIOp>(op.getLoc(), cond, cmp) : cmp;
71 map.
map(std::get<0>(bound), constant);
73 auto ifOp = b.
create<scf::IfOp>(op.getLoc(), cond,
true);
74 ifOp.getThenBodyBuilder().
clone(*op.getOperation(), map);
75 ifOp.getElseBodyBuilder().
clone(*op.getOperation());
84 auto bound = op.getUpperBound();
85 auto minOp = bound.getDefiningOp<AffineMinOp>();
89 for (
AffineExpr expr : minOp.getMap().getResults()) {
98 Value constant = b.
create<arith::ConstantIndexOp>(op.getLoc(), minConstant);
99 Value cond = b.
create<arith::CmpIOp>(op.getLoc(), arith::CmpIPredicate::eq,
101 map.
map(bound, constant);
102 auto ifOp = b.
create<scf::IfOp>(op.getLoc(), cond,
true);
103 ifOp.getThenBodyBuilder().
clone(*op.getOperation(), map);
104 ifOp.getElseBodyBuilder().
clone(*op.getOperation());
120 ForOp &partialIteration,
Value &splitBound) {
121 RewriterBase::InsertionGuard guard(b);
128 if (stepInt && *stepInt <= 1)
133 if (lbInt && ubInt && stepInt && (*ubInt - *lbInt) % *stepInt == 0)
142 if (
auto constExpr = dyn_cast<AffineConstantExpr>(map.
getResult(0)))
143 if (constExpr.getValue() == 0)
147 auto modMap =
AffineMap::get(0, 3, {sym1 - ((sym1 - sym0) % sym2)});
149 auto loc = forOp.getLoc();
152 forOp.getUpperBound(),
157 partialIteration = cast<ForOp>(b.
clone(*forOp.getOperation()));
158 partialIteration.getLowerBoundMutable().assign(splitBound);
160 partialIteration.getInitArgsMutable().assign(forOp->getResults());
164 [&]() { forOp.getUpperBoundMutable().assign(splitBound); });
170 ForOp partialIteration,
172 Value mainIv = forOp.getInductionVar();
173 Value partialIv = partialIteration.getInductionVar();
174 assert(forOp.getStep() == partialIteration.getStep() &&
175 "expected same step in main and partial loop");
176 Value step = forOp.getStep();
179 if (!isa<AffineMinOp, AffineMaxOp>(affineOp))
186 partialIteration.walk([&](
Operation *affineOp) {
187 if (!isa<AffineMinOp, AffineMaxOp>(affineOp))
197 ForOp &partialIteration) {
198 Value previousUb = forOp.getUpperBound();
200 if (failed(
peelForLoop(rewriter, forOp, partialIteration, splitBound)))
215 ForOp &firstIteration) {
216 RewriterBase::InsertionGuard guard(b);
222 if (lbInt && ubInt && stepInt &&
ceil(
float(*ubInt - *lbInt) / *stepInt) <= 1)
231 auto loc = forOp.getLoc();
233 loc, ubMap,
ValueRange{forOp.getLowerBound(), forOp.getStep()});
237 map.
map(forOp.getUpperBound(), splitBound);
238 firstIteration = cast<ForOp>(b.
clone(*forOp.getOperation(), map));
242 forOp.getInitArgsMutable().assign(firstIteration->getResults());
243 forOp.getLowerBoundMutable().assign(splitBound);
254 ForLoopPeelingPattern(
MLIRContext *ctx,
bool peelFront,
bool skipPartial)
256 skipPartial(skipPartial) {}
258 LogicalResult matchAndRewrite(ForOp forOp,
264 scf::ForOp partialIteration;
312 struct ParallelLoopSpecialization
313 :
public impl::SCFParallelLoopSpecializationBase<
314 ParallelLoopSpecialization> {
315 void runOnOperation()
override {
316 getOperation()->walk(
321 struct ForLoopSpecialization
322 :
public impl::SCFForLoopSpecializationBase<ForLoopSpecialization> {
323 void runOnOperation()
override {
328 struct ForLoopPeeling :
public impl::SCFForLoopPeelingBase<ForLoopPeeling> {
329 void runOnOperation()
override {
330 auto *parentOp = getOperation();
333 patterns.add<ForLoopPeelingPattern>(ctx, peelFront, skipPartial);
346 return std::make_unique<ParallelLoopSpecialization>();
350 return std::make_unique<ForLoopSpecialization>();
354 return std::make_unique<ForLoopPeeling>();
static void specializeForLoopForUnrolling(ForOp op)
Rewrite a for loop with bounds defined by an affine.min with a constant into 2 loops after checking i...
static void specializeParallelLoopForUnrolling(ParallelOp op)
Rewrite a parallel loop with bounds defined by an affine.min with a constant into 2 loops after check...
static constexpr char kPeeledLoopLabel[]
static void rewriteAffineOpAfterPeeling(RewriterBase &rewriter, ForOp forOp, ForOp partialIteration, Value previousUb)
static LogicalResult peelForLoop(RewriterBase &b, ForOp forOp, ForOp &partialIteration, Value &splitBound)
Rewrite a for loop with bounds/step that potentially do not divide evenly into a for loop where the s...
static constexpr char kPartialIterationLabel[]
static Value max(ImplicitLocOpBuilder &builder, Value value, Value bound)
static Value min(ImplicitLocOpBuilder &builder, Value value, Value bound)
Base type for affine expression.
A multi-dimensional affine map Affine map's are immutable like Type's, and they are uniqued.
static AffineMap get(MLIRContext *context)
Returns a zero result affine map with no dimensions or symbols: () -> ().
AffineExpr getResult(unsigned idx) const
MLIRContext * getContext() const
This is a utility class for mapping one set of IR entities to another.
void map(Value from, Value to)
Inserts a new mapping for 'from' to 'to'.
MLIRContext is the top-level object for a collection of MLIR operations.
This class helps build Operations.
Operation * clone(Operation &op, IRMapping &mapper)
Creates a deep copy of the specified operation, remapping any operands that use values outside of the...
void setInsertionPoint(Block *block, Block::iterator insertPoint)
Set the insertion point to the specified location.
void createOrFold(SmallVectorImpl< Value > &results, Location location, Args &&...args)
Create an operation of specific op type at the current insertion point, and immediately try to fold i...
Operation * create(const OperationState &state)
Creates an operation given the fields represented as an OperationState.
void setInsertionPointAfter(Operation *op)
Sets the insertion point to the node after the specified operation, which will cause subsequent inser...
Operation is the basic unit of execution within MLIR.
bool hasAttr(StringAttr name)
Return true if the operation has an attribute with the provided name, false otherwise.
Operation * clone(IRMapping &mapper, CloneOptions options=CloneOptions::all())
Create a deep copy of this operation, remapping any operands that use values outside of the operation...
OpTy getParentOfType()
Return the closest surrounding parent operation that is of type 'OpTy'.
Attribute removeAttr(StringAttr name)
Remove the attribute with the specified name if it exists.
void erase()
Remove this operation from its parent block and delete it.
A special type of RewriterBase that coordinates the application of a rewrite pattern on the current I...
This class coordinates the application of a rewrite on a set of IR, providing a way for clients to tr...
void replaceAllUsesWith(Value from, Value to)
Find uses of from and replace them with to.
void modifyOpInPlace(Operation *root, CallableT &&callable)
This method is a utility wrapper around an in-place modification of an operation.
This class provides an abstraction over the different types of ranges over Values.
This class represents an instance of an SSA value in the MLIR system, representing a computable value...
static WalkResult advance()
void fullyComposeAffineMapAndOperands(AffineMap *map, SmallVectorImpl< Value > *operands)
Given an affine map map and its input operands, this method composes into map, maps of AffineApplyOps...
DynamicAPInt ceil(const Fraction &f)
LogicalResult peelForLoopAndSimplifyBounds(RewriterBase &rewriter, ForOp forOp, scf::ForOp &partialIteration)
Rewrite a for loop with bounds/step that potentially do not divide evenly into a for loop where the s...
LogicalResult peelForLoopFirstIteration(RewriterBase &rewriter, ForOp forOp, scf::ForOp &partialIteration)
Peel the first iteration out of the scf.for loop.
LogicalResult rewritePeeledMinMaxOp(RewriterBase &rewriter, Operation *op, Value iv, Value ub, Value step, bool insideLoop)
Try to simplify the given affine.min/max operation op after loop peeling.
Value constantIndex(OpBuilder &builder, Location loc, int64_t i)
Generates a constant of index type.
Include the generated interface declarations.
std::unique_ptr< Pass > createParallelLoopSpecializationPass()
Creates a pass that specializes parallel loop for unrolling and vectorization.
std::unique_ptr< Pass > createForLoopSpecializationPass()
Creates a pass that specializes for loop for unrolling and vectorization.
std::optional< int64_t > getConstantIntValue(OpFoldResult ofr)
If ofr is a constant integer or an IntegerAttr, return the integer.
LogicalResult applyPatternsGreedily(Region ®ion, const FrozenRewritePatternSet &patterns, GreedyRewriteConfig config=GreedyRewriteConfig(), bool *changed=nullptr)
Rewrite ops in the given region, which must be isolated from above, by repeatedly applying the highes...
std::unique_ptr< Pass > createForLoopPeelingPass()
Creates a pass that peels for loops at their upper bounds for better vectorization.
const FrozenRewritePatternSet & patterns
void bindSymbols(MLIRContext *ctx, AffineExprTy &...exprs)
Bind a list of AffineExpr references to SymbolExpr at positions: [0 .
OpRewritePattern is a wrapper around RewritePattern that allows for matching and rewriting against an...