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//===- AffineAnalysis.h - analyses for affine structures --------*- C++ -*-===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// This header file defines prototypes for methods that perform analysis
// involving affine structures (AffineExprStorage, AffineMap, IntegerSet, etc.)
// and other IR structures that in turn use these.
//
//===----------------------------------------------------------------------===//
#ifndef MLIR_ANALYSIS_AFFINE_ANALYSIS_H
#define MLIR_ANALYSIS_AFFINE_ANALYSIS_H
#include "mlir/Dialect/StandardOps/IR/Ops.h"
#include "mlir/IR/Value.h"
#include "llvm/ADT/Optional.h"
#include "llvm/ADT/SmallVector.h"
namespace mlir {
class AffineApplyOp;
class AffineForOp;
class AffineValueMap;
class FlatAffineRelation;
class FlatAffineValueConstraints;
class Operation;
/// A description of a (parallelizable) reduction in an affine loop.
struct LoopReduction {
/// Reduction kind.
AtomicRMWKind kind;
/// Position of the iteration argument that acts as accumulator.
unsigned iterArgPosition;
/// The value being reduced.
Value value;
};
/// Populate `supportedReductions` with descriptors of the supported reductions.
void getSupportedReductions(
AffineForOp forOp, SmallVectorImpl<LoopReduction> &supportedReductions);
/// Returns true if `forOp' is a parallel loop. If `parallelReductions` is
/// provided, populates it with descriptors of the parallelizable reductions and
/// treats them as not preventing parallelization.
bool isLoopParallel(
AffineForOp forOp,
SmallVectorImpl<LoopReduction> *parallelReductions = nullptr);
/// Returns true if `forOp' doesn't have memory dependences preventing
/// parallelization. This function doesn't check iter_args and should be used
/// only as a building block for full parallel-checking functions.
bool isLoopMemoryParallel(AffineForOp forOp);
/// Returns in `affineApplyOps`, the sequence of those AffineApplyOp
/// Operations that are reachable via a search starting from `operands` and
/// ending at those operands that are not the result of an AffineApplyOp.
void getReachableAffineApplyOps(ArrayRef<Value> operands,
SmallVectorImpl<Operation *> &affineApplyOps);
/// Builds a system of constraints with dimensional identifiers corresponding to
/// the loop IVs of the forOps and AffineIfOp's operands appearing in
/// that order. Bounds of the loop are used to add appropriate inequalities.
/// Constraints from the index sets of AffineIfOp are also added. Any symbols
/// founds in the bound operands are added as symbols in the system. Returns
/// failure for the yet unimplemented cases. `ops` accepts both AffineForOp and
/// AffineIfOp.
// TODO: handle non-unit strides.
LogicalResult getIndexSet(MutableArrayRef<Operation *> ops,
FlatAffineValueConstraints *domain);
/// Encapsulates a memref load or store access information.
struct MemRefAccess {
Value memref;
Operation *opInst;
SmallVector<Value, 4> indices;
/// Constructs a MemRefAccess from a load or store operation.
// TODO: add accessors to standard op's load, store, DMA op's to return
// MemRefAccess, i.e., loadOp->getAccess(), dmaOp->getRead/WriteAccess.
explicit MemRefAccess(Operation *opInst);
// Returns the rank of the memref associated with this access.
unsigned getRank() const;
// Returns true if this access is of a store op.
bool isStore() const;
/// Creates an access relation for the access. An access relation maps
/// elements of an iteration domain to the element(s) of an array domain
/// accessed by that iteration of the associated statement through some array
/// reference. For example, given the MLIR code:
///
/// affine.for %i0 = 0 to 10 {
/// affine.for %i1 = 0 to 10 {
/// %a = affine.load %arr[%i0 + %i1, %i0 + 2 * %i1] : memref<100x100xf32>
/// }
/// }
///
/// The access relation, assuming that the memory locations for %arr are
/// represented as %m0, %m1 would be:
///
/// (%i0, %i1) -> (%m0, %m1)
/// %m0 = %i0 + %i1
/// %m1 = %i0 + 2 * %i1
/// 0 <= %i0 < 10
/// 0 <= %i1 < 10
///
/// Returns failure for yet unimplemented/unsupported cases (see docs of
/// mlir::getIndexSet and mlir::getRelationFromMap for these cases).
LogicalResult getAccessRelation(FlatAffineRelation &accessRel) const;
/// Populates 'accessMap' with composition of AffineApplyOps reachable from
/// 'indices'.
void getAccessMap(AffineValueMap *accessMap) const;
/// Equal if both affine accesses can be proved to be equivalent at compile
/// time (considering the memrefs, their respective affine access maps and
/// operands). The equality of access functions + operands is checked by
/// subtracting fully composed value maps, and then simplifying the difference
/// using the expression flattener.
/// TODO: this does not account for aliasing of memrefs.
bool operator==(const MemRefAccess &rhs) const;
bool operator!=(const MemRefAccess &rhs) const { return !(*this == rhs); }
};
// DependenceComponent contains state about the direction of a dependence as an
// interval [lb, ub] for an AffineForOp.
// Distance vectors components are represented by the interval [lb, ub] with
// lb == ub.
// Direction vectors components are represented by the interval [lb, ub] with
// lb < ub. Note that ub/lb == None means unbounded.
struct DependenceComponent {
// The AffineForOp Operation associated with this dependence component.
Operation *op;
// The lower bound of the dependence distance.
Optional<int64_t> lb;
// The upper bound of the dependence distance (inclusive).
Optional<int64_t> ub;
DependenceComponent() : lb(llvm::None), ub(llvm::None) {}
};
/// Checks whether two accesses to the same memref access the same element.
/// Each access is specified using the MemRefAccess structure, which contains
/// the operation, indices and memref associated with the access. Returns
/// 'NoDependence' if it can be determined conclusively that the accesses do not
/// access the same memref element. If 'allowRAR' is true, will consider
/// read-after-read dependences (typically used by applications trying to
/// optimize input reuse).
// TODO: Wrap 'dependenceConstraints' and 'dependenceComponents' into a single
// struct.
// TODO: Make 'dependenceConstraints' optional arg.
struct DependenceResult {
enum ResultEnum {
HasDependence, // A dependence exists between 'srcAccess' and 'dstAccess'.
NoDependence, // No dependence exists between 'srcAccess' and 'dstAccess'.
Failure, // Dependence check failed due to unsupported cases.
} value;
DependenceResult(ResultEnum v) : value(v) {}
};
DependenceResult checkMemrefAccessDependence(
const MemRefAccess &srcAccess, const MemRefAccess &dstAccess,
unsigned loopDepth, FlatAffineValueConstraints *dependenceConstraints,
SmallVector<DependenceComponent, 2> *dependenceComponents,
bool allowRAR = false);
/// Utility function that returns true if the provided DependenceResult
/// corresponds to a dependence result.
inline bool hasDependence(DependenceResult result) {
return result.value == DependenceResult::HasDependence;
}
/// Returns in 'depCompsVec', dependence components for dependences between all
/// load and store ops in loop nest rooted at 'forOp', at loop depths in range
/// [1, maxLoopDepth].
void getDependenceComponents(
AffineForOp forOp, unsigned maxLoopDepth,
std::vector<SmallVector<DependenceComponent, 2>> *depCompsVec);
} // end namespace mlir
#endif // MLIR_ANALYSIS_AFFINE_ANALYSIS_H