Jim Kitchen 81d0d2b2a0 [mlir][sparse] Sparse reduction in lex order no longer produces dense output
Previously, when performing a reduction on a sparse tensor, the result
would be different depending on iteration order. For expanded access pattern,
an empty row would contribute no entry in the output. For lex ordering, the
identity would end up in the output.

This code changes that behavior and keeps track of whether any entries were
actually reduced in lex ordering, making the output consistent between the
two iteration styles.

Differential Revision: https://reviews.llvm.org/D142050
2023-02-10 13:09:28 -06:00

191 lines
6.3 KiB
C++

//===- CodegenEnv.h - Code generation environment class ---------*- 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 the code generation environment class.
//
//===----------------------------------------------------------------------===//
#ifndef MLIR_DIALECT_SPARSETENSOR_TRANSFORMS_CODEGENENV_H_
#define MLIR_DIALECT_SPARSETENSOR_TRANSFORMS_CODEGENENV_H_
#include "CodegenUtils.h"
#include "LoopEmitter.h"
#include "mlir/Dialect/Linalg/IR/Linalg.h"
#include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"
#include "mlir/Dialect/SparseTensor/Transforms/Passes.h"
#include "mlir/Dialect/SparseTensor/Utils/Merger.h"
#include <optional>
namespace mlir {
namespace sparse_tensor {
/// The code generation environment class aggregates a number of data
/// structures that are needed during the code generation phase of
/// sparsification. This environment simplifies passing around such
/// data during sparsification (rather than passing around all the
/// individual compoments where needed). Furthermore, it provides
/// convience methods that keep implementation details transparent
/// to sparsification while asserting on internal consistency.
class CodegenEnv {
public:
/// Constructs a code generation environment which can be
/// passed around during sparsification for bookkeeping
/// together with some consistency asserts.
CodegenEnv(linalg::GenericOp linop, SparsificationOptions opts,
unsigned numTensors, unsigned numLoops, unsigned numFilterLoops);
//
// General methods.
//
LogicalResult initTensorExp();
unsigned getTensorExp() const { return tensorExp; }
linalg::GenericOp op() const { return linalgOp; }
const SparsificationOptions &options() const { return sparseOptions; }
Merger &merger() { return latticeMerger; }
LoopEmitter &emitter() { return loopEmitter; }
void startEmit();
/// Generates loop boundary statements (entering/exiting loops). The function
/// passes and updates the passed-in parameters.
std::optional<Operation *>
genLoopBoundary(function_ref<
std::optional<Operation *>(MutableArrayRef<Value> parameters)>
callback);
//
// Merger delegates.
//
TensorExp &exp(unsigned e) { return latticeMerger.exp(e); }
LatPoint &lat(unsigned l) { return latticeMerger.lat(l); }
SmallVector<unsigned> &set(unsigned s) { return latticeMerger.set(s); }
DimLevelType dlt(unsigned t, unsigned i) const {
return latticeMerger.getDimLevelType(t, i);
}
DimLevelType dlt(unsigned b) const {
return latticeMerger.getDimLevelType(b);
}
//
// Code generation environment verify functions.
//
/// Whether the tensor expression is admissible for codegen.
/// It also sets the sparseOut if the output tensor is sparse.
bool isAdmissibleTensorExp(unsigned exp);
/// Whether the iteration graph is sorted in admissible topoOrder.
/// Sets outerParNest on success with sparse output
bool isAdmissibleTopoOrder();
//
// Topological delegate and sort methods.
//
size_t topSortSize() const { return topSort.size(); }
unsigned topSortAt(unsigned i) const { return topSort.at(i); }
void topSortPushBack(unsigned i) { topSort.push_back(i); }
void topSortClear(unsigned capacity = 0) {
topSort.clear();
topSort.reserve(capacity);
}
ArrayRef<unsigned> getTopSortSlice(size_t n, size_t m) const;
ArrayRef<unsigned> getLoopCurStack() const;
Value getLoopIdxValue(size_t loopIdx) const;
//
// Sparse tensor output and expansion methods.
//
bool hasSparseOutput() const { return sparseOut != nullptr; }
bool isSparseOutput(OpOperand *o) const { return sparseOut == o; }
Value getInsertionChain() const { return insChain; }
void updateInsertionChain(Value chain);
bool atExpandLevel(OpOperand *o, unsigned rank, unsigned lv) const;
void startExpand(Value values, Value filled, Value added, Value count);
bool isExpand() const { return expValues != nullptr; }
void updateExpandCount(Value count);
Value getExpandValues() const { return expValues; }
Value getExpandFilled() const { return expFilled; }
Value getExpandAdded() const { return expAdded; }
Value getExpandCount() const { return expCount; }
void endExpand();
//
// Reduction methods.
//
void startReduc(unsigned exp, Value val);
bool isReduc() const { return redExp != -1u; }
void updateReduc(Value val);
Value getReduc() const { return redVal; }
Value endReduc();
void setValidLexInsert(Value val);
void clearValidLexInsert();
Value getValidLexInsert() const { return redValidLexInsert; }
void startCustomReduc(unsigned exp);
bool isCustomReduc() const { return redCustom != -1u; }
Value getCustomRedId();
void endCustomReduc();
private:
// Linalg operation.
linalg::GenericOp linalgOp;
// Sparsification options.
SparsificationOptions sparseOptions;
// Merger helper class.
Merger latticeMerger;
// Loop emitter helper class.
LoopEmitter loopEmitter;
// Topological sort.
std::vector<unsigned> topSort;
// Sparse tensor as output. Implemented either through direct injective
// insertion in lexicographic index order or through access pattern
// expansion in the innermost loop nest (`expValues` through `expCount`).
OpOperand *sparseOut;
unsigned outerParNest;
Value insChain;
Value expValues;
Value expFilled;
Value expAdded;
Value expCount;
// Bookkeeping for reductions (up-to-date value of the reduction, and indices
// into the merger's expression tree. When the indices of a tensor reduction
// expression are exhausted, all inner loops can use a scalarized reduction.
Value redVal;
unsigned redExp;
unsigned redCustom;
// Bookkeeping for lex insertion during reductions. Holds the runtime boolean
// value of whether any reduction occurred. This is only set during a
// reduction and cleared once the reduction is finished.
Value redValidLexInsert;
// The root tensor expression of the kernel.
unsigned tensorExp;
};
} // namespace sparse_tensor
} // namespace mlir
#endif // MLIR_DIALECT_SPARSETENSOR_TRANSFORMS_CODEGENENV_H_