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//===- Utils.h - General analysis utilities ---------------------*- C++ -*-===//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
// This header file defines prototypes for various transformation utilities for
// memref's and non-loop IR structures. These are not passes by themselves but
// are used either by passes, optimization sequences, or in turn by other
// transformation utilities.
#include "mlir/Analysis/AffineStructures.h"
#include "mlir/IR/AffineMap.h"
#include "mlir/IR/Block.h"
#include "mlir/IR/Location.h"
#include "mlir/Support/LLVM.h"
#include "llvm/ADT/SmallVector.h"
#include <memory>
namespace mlir {
class AffineForOp;
class Block;
class Location;
struct MemRefAccess;
class Operation;
class Value;
/// Populates 'loops' with IVs of the loops surrounding 'op' ordered from
/// the outermost 'affine.for' operation to the innermost one.
// TODO: handle 'affine.if' ops.
void getLoopIVs(Operation &op, SmallVectorImpl<AffineForOp> *loops);
/// Populates 'ops' with IVs of the loops surrounding `op`, along with
/// `affine.if` operations interleaved between these loops, ordered from the
/// outermost `affine.for` or `affine.if` operation to the innermost one.
void getEnclosingAffineForAndIfOps(Operation &op,
SmallVectorImpl<Operation *> *ops);
/// Returns the nesting depth of this operation, i.e., the number of loops
/// surrounding this operation.
unsigned getNestingDepth(Operation *op);
/// Returns whether a loop is a parallel loop and contains a reduction loop.
bool isLoopParallelAndContainsReduction(AffineForOp forOp);
/// Returns in 'sequentialLoops' all sequential loops in loop nest rooted
/// at 'forOp'.
void getSequentialLoops(AffineForOp forOp,
llvm::SmallDenseSet<Value, 8> *sequentialLoops);
/// Enumerates different result statuses of slice computation by
/// `computeSliceUnion`
// TODO: Identify and add different kinds of failures during slice computation.
struct SliceComputationResult {
enum ResultEnum {
IncorrectSliceFailure, // Slice is computed, but it is incorrect.
GenericFailure, // Unable to compute src loop computation slice.
} value;
SliceComputationResult(ResultEnum v) : value(v) {}
/// ComputationSliceState aggregates loop IVs, loop bound AffineMaps and their
/// associated operands for a set of loops within a loop nest (typically the
/// set of loops surrounding a store operation). Loop bound AffineMaps which
/// are non-null represent slices of that loop's iteration space.
struct ComputationSliceState {
// List of sliced loop IVs (ordered from outermost to innermost).
// EX: 'ivs[i]' has lower bound 'lbs[i]' and upper bound 'ubs[i]'.
SmallVector<Value, 4> ivs;
// List of lower bound AffineMaps.
SmallVector<AffineMap, 4> lbs;
// List of upper bound AffineMaps.
SmallVector<AffineMap, 4> ubs;
// List of lower bound operands (lbOperands[i] are used by 'lbs[i]').
std::vector<SmallVector<Value, 4>> lbOperands;
// List of upper bound operands (ubOperands[i] are used by 'ubs[i]').
std::vector<SmallVector<Value, 4>> ubOperands;
// Slice loop nest insertion point in target loop nest.
Block::iterator insertPoint;
// Adds to 'cst' with constraints which represent the slice bounds on 'ivs'
// in 'this'. Specifically, the values in 'ivs' are added to 'cst' as dim
// identifiers and the values in 'lb/ubOperands' are added as symbols.
// Constraints are added for all loop IV bounds (dim or symbol), and
// constraints are added for slice bounds in 'lbs'/'ubs'.
// Returns failure if we cannot add loop bounds because of unsupported cases.
LogicalResult getAsConstraints(FlatAffineValueConstraints *cst);
/// Adds to 'cst' constraints which represent the original loop bounds on
/// 'ivs' in 'this'. This corresponds to the original domain of the loop nest
/// from which the slice is being computed. Returns failure if we cannot add
/// loop bounds because of unsupported cases.
LogicalResult getSourceAsConstraints(FlatAffineValueConstraints &cst);
// Clears all bounds and operands in slice state.
void clearBounds();
/// Returns true if the computation slice is empty.
bool isEmpty() const { return ivs.empty(); }
/// Returns true if the computation slice encloses all the iterations of the
/// sliced loop nest. Returns false if it does not. Returns llvm::None if it
/// cannot determine if the slice is maximal or not.
// TODO: Cache 'isMaximal' so that we don't recompute it when the slice
// information hasn't changed.
Optional<bool> isMaximal() const;
/// Checks the validity of the slice computed. This is done using the
/// following steps:
/// 1. Get the new domain of the slice that would be created if fusion
/// succeeds. This domain gets constructed with source loop IVS and
/// destination loop IVS as dimensions.
/// 2. Project out the dimensions of the destination loop from the domain
/// above calculated in step(1) to express it purely in terms of the source
/// loop IVs.
/// 3. Calculate a set difference between the iterations of the new domain and
/// the original domain of the source loop.
/// If this difference is empty, the slice is declared to be valid. Otherwise,
/// return false as it implies that the effective fusion results in at least
/// one iteration of the slice that was not originally in the source's domain.
/// If the validity cannot be determined, returns llvm:None.
Optional<bool> isSliceValid();
void dump() const;
/// Fast check to determine if the computation slice is maximal. Returns true
/// if each slice dimension maps to an existing dst dimension and both the src
/// and the dst loops for those dimensions have the same bounds. Returns false
/// if both the src and the dst loops don't have the same bounds. Returns
/// llvm::None if none of the above can be proven.
Optional<bool> isSliceMaximalFastCheck() const;
/// Computes the computation slice loop bounds for one loop nest as affine maps
/// of the other loop nest's IVs and symbols, using 'dependenceConstraints'
/// computed between 'depSourceAccess' and 'depSinkAccess'.
/// If 'isBackwardSlice' is true, a backwards slice is computed in which the
/// slice bounds of loop nest surrounding 'depSourceAccess' are computed in
/// terms of loop IVs and symbols of the loop nest surrounding 'depSinkAccess'
/// at 'loopDepth'.
/// If 'isBackwardSlice' is false, a forward slice is computed in which the
/// slice bounds of loop nest surrounding 'depSinkAccess' are computed in terms
/// of loop IVs and symbols of the loop nest surrounding 'depSourceAccess' at
/// 'loopDepth'.
/// The slice loop bounds and associated operands are returned in 'sliceState'.
// Backward slice example:
// affine.for %i0 = 0 to 10 {
// %cst, %0[%i0] : memref<100xf32> // 'depSourceAccess'
// }
// affine.for %i1 = 0 to 10 {
// %v = affine.load %0[%i1] : memref<100xf32> // 'depSinkAccess'
// }
// // Backward computation slice of loop nest '%i0'.
// affine.for %i0 = (d0) -> (d0)(%i1) to (d0) -> (d0 + 1)(%i1) {
// %cst, %0[%i0] : memref<100xf32> // 'depSourceAccess'
// }
// Forward slice example:
// affine.for %i0 = 0 to 10 {
// %cst, %0[%i0] : memref<100xf32> // 'depSourceAccess'
// }
// affine.for %i1 = 0 to 10 {
// %v = affine.load %0[%i1] : memref<100xf32> // 'depSinkAccess'
// }
// // Forward computation slice of loop nest '%i1'.
// affine.for %i1 = (d0) -> (d0)(%i0) to (d0) -> (d0 + 1)(%i0) {
// %v = affine.load %0[%i1] : memref<100xf32> // 'depSinkAccess'
// }
void getComputationSliceState(Operation *depSourceOp, Operation *depSinkOp,
FlatAffineValueConstraints *dependenceConstraints,
unsigned loopDepth, bool isBackwardSlice,
ComputationSliceState *sliceState);
/// Return the number of iterations for the `slicetripCountMap` provided.
uint64_t getSliceIterationCount(
const llvm::SmallDenseMap<Operation *, uint64_t, 8> &sliceTripCountMap);
/// Builds a map 'tripCountMap' from AffineForOp to constant trip count for
/// loop nest surrounding represented by slice loop bounds in 'slice'. Returns
/// true on success, false otherwise (if a non-constant trip count was
/// encountered).
bool buildSliceTripCountMap(
const ComputationSliceState &slice,
llvm::SmallDenseMap<Operation *, uint64_t, 8> *tripCountMap);
/// Computes in 'sliceUnion' the union of all slice bounds computed at
/// 'loopDepth' between all dependent pairs of ops in 'opsA' and 'opsB', and
/// then verifies if it is valid. The parameter 'numCommonLoops' is the number
/// of loops common to the operations in 'opsA' and 'opsB'. If 'isBackwardSlice'
/// is true, computes slice bounds for loop nest surrounding ops in 'opsA', as a
/// function of IVs and symbols of loop nest surrounding ops in 'opsB' at
/// 'loopDepth'. If 'isBackwardSlice' is false, computes slice bounds for loop
/// nest surrounding ops in 'opsB', as a function of IVs and symbols of loop
/// nest surrounding ops in 'opsA' at 'loopDepth'. Returns
/// 'SliceComputationResult::Success' if union was computed correctly, an
/// appropriate 'failure' otherwise.
// TODO: Change this API to take 'forOpA'/'forOpB'.
computeSliceUnion(ArrayRef<Operation *> opsA, ArrayRef<Operation *> opsB,
unsigned loopDepth, unsigned numCommonLoops,
bool isBackwardSlice, ComputationSliceState *sliceUnion);
/// Creates a clone of the computation contained in the loop nest surrounding
/// 'srcOpInst', slices the iteration space of src loop based on slice bounds
/// in 'sliceState', and inserts the computation slice at the beginning of the
/// operation block of the loop at 'dstLoopDepth' in the loop nest surrounding
/// 'dstOpInst'. Returns the top-level loop of the computation slice on
/// success, returns nullptr otherwise.
// Loop depth is a crucial optimization choice that determines where to
// materialize the results of the backward slice - presenting a trade-off b/w
// storage and redundant computation in several cases.
// TODO: Support computation slices with common surrounding loops.
AffineForOp insertBackwardComputationSlice(Operation *srcOpInst,
Operation *dstOpInst,
unsigned dstLoopDepth,
ComputationSliceState *sliceState);
/// A region of a memref's data space; this is typically constructed by
/// analyzing load/store op's on this memref and the index space of loops
/// surrounding such op's.
// For example, the memref region for a load operation at loop depth = 1:
// affine.for %i = 0 to 32 {
// affine.for %ii = %i to (d0) -> (d0 + 8) (%i) {
// affine.load %A[%ii]
// }
// }
// Region: {memref = %A, write = false, {%i <= m0 <= %i + 7} }
// The last field is a 2-d FlatAffineValueConstraints symbolic in %i.
struct MemRefRegion {
explicit MemRefRegion(Location loc) : loc(loc) {}
/// Computes the memory region accessed by this memref with the region
/// represented as constraints symbolic/parametric in 'loopDepth' loops
/// surrounding opInst. The computed region's 'cst' field has exactly as many
/// dimensional identifiers as the rank of the memref, and *potentially*
/// additional symbolic identifiers which could include any of the loop IVs
/// surrounding opInst up until 'loopDepth' and another additional Function
/// symbols involved with the access (for eg., those appear in affine.apply's,
/// loop bounds, etc.). If 'sliceState' is non-null, operands from
/// 'sliceState' are added as symbols, and the following constraints are added
/// to the system:
/// *) Inequality constraints which represent loop bounds for 'sliceState'
/// operands which are loop IVS (these represent the destination loop IVs
/// of the slice, and are added as symbols to MemRefRegion's constraint
/// system).
/// *) Inequality constraints for the slice bounds in 'sliceState', which
/// represent the bounds on the loop IVs in this constraint system w.r.t
/// to slice operands (which correspond to symbols).
/// If 'addMemRefDimBounds' is true, constant upper/lower bounds
/// [0, memref.getDimSize(i)) are added for each MemRef dimension 'i'.
/// For example, the memref region for this operation at loopDepth = 1 will
/// be:
/// affine.for %i = 0 to 32 {
/// affine.for %ii = %i to (d0) -> (d0 + 8) (%i) {
/// load %A[%ii]
/// }
/// }
/// {memref = %A, write = false, {%i <= m0 <= %i + 7} }
/// The last field is a 2-d FlatAffineValueConstraints symbolic in %i.
LogicalResult compute(Operation *op, unsigned loopDepth,
const ComputationSliceState *sliceState = nullptr,
bool addMemRefDimBounds = true);
FlatAffineValueConstraints *getConstraints() { return &cst; }
const FlatAffineValueConstraints *getConstraints() const { return &cst; }
bool isWrite() const { return write; }
void setWrite(bool flag) { write = flag; }
/// Returns a constant upper bound on the number of elements in this region if
/// bounded by a known constant (always possible for static shapes), None
/// otherwise. Note that the symbols of the region are treated specially,
/// i.e., the returned bounding constant holds for *any given* value of the
/// symbol identifiers. The 'shape' vector is set to the corresponding
/// dimension-wise bounds major to minor. The number of elements and all the
/// dimension-wise bounds are guaranteed to be non-negative. We use int64_t
/// instead of uint64_t since index types can be at most int64_t. `lbs` are
/// set to the lower bounds for each of the rank dimensions, and lbDivisors
/// contains the corresponding denominators for floorDivs.
Optional<int64_t> getConstantBoundingSizeAndShape(
SmallVectorImpl<int64_t> *shape = nullptr,
std::vector<SmallVector<int64_t, 4>> *lbs = nullptr,
SmallVectorImpl<int64_t> *lbDivisors = nullptr) const;
/// Gets the lower and upper bound map for the dimensional identifier at
/// `pos`.
void getLowerAndUpperBound(unsigned pos, AffineMap &lbMap,
AffineMap &ubMap) const;
/// A wrapper around FlatAffineValueConstraints::getConstantBoundOnDimSize().
/// 'pos' corresponds to the position of the memref shape's dimension (major
/// to minor) which matches 1:1 with the dimensional identifier positions in
/// 'cst'.
getConstantBoundOnDimSize(unsigned pos,
SmallVectorImpl<int64_t> *lb = nullptr,
int64_t *lbFloorDivisor = nullptr) const {
assert(pos < getRank() && "invalid position");
return cst.getConstantBoundOnDimSize(pos, lb);
/// Returns the size of this MemRefRegion in bytes.
Optional<int64_t> getRegionSize();
// Wrapper around FlatAffineValueConstraints::unionBoundingBox.
LogicalResult unionBoundingBox(const MemRefRegion &other);
/// Returns the rank of the memref that this region corresponds to.
unsigned getRank() const;
/// Memref that this region corresponds to.
Value memref;
/// Read or write.
bool write;
/// If there is more than one load/store op associated with the region, the
/// location information would correspond to one of those op's.
Location loc;
/// Region (data space) of the memref accessed. This set will thus have at
/// least as many dimensional identifiers as the shape dimensionality of the
/// memref, and these are the leading dimensions of the set appearing in that
/// order (major to minor / outermost to innermost). There may be additional
/// identifiers since getMemRefRegion() is called with a specific loop depth,
/// and thus the region is symbolic in the outer surrounding loops at that
/// depth.
// TODO: Replace this to exploit HyperRectangularSet.
FlatAffineValueConstraints cst;
/// Returns the size of memref data in bytes if it's statically shaped, None
/// otherwise.
Optional<uint64_t> getMemRefSizeInBytes(MemRefType memRefType);
/// Checks a load or store op for an out of bound access; returns failure if the
/// access is out of bounds along any of the dimensions, success otherwise.
/// Emits a diagnostic error (with location information) if emitError is true.
template <typename LoadOrStoreOpPointer>
LogicalResult boundCheckLoadOrStoreOp(LoadOrStoreOpPointer loadOrStoreOp,
bool emitError = true);
/// Returns the number of surrounding loops common to both A and B.
unsigned getNumCommonSurroundingLoops(Operation &A, Operation &B);
/// Gets the memory footprint of all data touched in the specified memory space
/// in bytes; if the memory space is unspecified, considers all memory spaces.
Optional<int64_t> getMemoryFootprintBytes(AffineForOp forOp,
int memorySpace = -1);
/// Simplify the integer set by simplifying the underlying affine expressions by
/// flattening and some simple inference. Also, drop any duplicate constraints.
/// Returns the simplified integer set. This method runs in time linear in the
/// number of constraints.
IntegerSet simplifyIntegerSet(IntegerSet set);
/// Returns the innermost common loop depth for the set of operations in 'ops'.
unsigned getInnermostCommonLoopDepth(
ArrayRef<Operation *> ops,
SmallVectorImpl<AffineForOp> *surroundingLoops = nullptr);
} // end namespace mlir