[Mlir-commits] [mlir] [MLIR][SparseTensor] Dense Outer Loop Ordering Strategy (PR #160168)
Govind Malasani
llvmlistbot at llvm.org
Thu Oct 2 16:43:56 PDT 2025
https://github.com/gmalasan updated https://github.com/llvm/llvm-project/pull/160168
>From 9a776774a8b2b028287f37b932453dc0d855d249 Mon Sep 17 00:00:00 2001
From: gmalasan <145235389+gmalasan at users.noreply.github.com>
Date: Thu, 2 Oct 2025 19:37:48 -0400
Subject: [PATCH] [MLIR][SparseTensor] Add dense-outer loop ordering heuristic
---
.../Dialect/SparseTensor/Transforms/Passes.h | 21 ++++-
.../Dialect/SparseTensor/Transforms/Passes.td | 7 ++
.../Transforms/SparseReinterpretMap.cpp | 24 +++--
.../Transforms/SparseTensorPasses.cpp | 11 ++-
.../Transforms/Utils/IterationGraphSorter.cpp | 93 +++++++++++++++++--
.../Transforms/Utils/IterationGraphSorter.h | 17 +++-
6 files changed, 151 insertions(+), 22 deletions(-)
diff --git a/mlir/include/mlir/Dialect/SparseTensor/Transforms/Passes.h b/mlir/include/mlir/Dialect/SparseTensor/Transforms/Passes.h
index 212f7b6f13c26..b401458f5ddc5 100644
--- a/mlir/include/mlir/Dialect/SparseTensor/Transforms/Passes.h
+++ b/mlir/include/mlir/Dialect/SparseTensor/Transforms/Passes.h
@@ -55,6 +55,18 @@ enum class SparseEmitStrategy {
kDebugInterface, // generate only place-holder for sparse iteration
};
+namespace sparse_tensor {
+
+/// Defines a strategy for loop ordering during sparse code generation.
+enum class LoopOrderingStrategy : unsigned {
+ kDefault, ///< Default strategy (eagerly selects last loop in topological
+ ///< sort).
+ kDenseOuter, ///< Prefer dense, then sparse, then singleton dimensions
+ ///< outermost.
+};
+
+} // namespace sparse_tensor
+
#define GEN_PASS_DECL
#include "mlir/Dialect/SparseTensor/Transforms/Passes.h.inc"
@@ -71,11 +83,16 @@ std::unique_ptr<Pass> createSparseAssembler(bool directOut);
// The SparseReinterpretMap pass.
//===----------------------------------------------------------------------===//
-void populateSparseReinterpretMap(RewritePatternSet &patterns,
- ReinterpretMapScope scope);
+void populateSparseReinterpretMap(
+ RewritePatternSet &patterns, ReinterpretMapScope scope,
+ sparse_tensor::LoopOrderingStrategy strategy =
+ sparse_tensor::LoopOrderingStrategy::kDefault);
std::unique_ptr<Pass> createSparseReinterpretMapPass();
std::unique_ptr<Pass> createSparseReinterpretMapPass(ReinterpretMapScope scope);
+std::unique_ptr<Pass>
+createSparseReinterpretMapPass(ReinterpretMapScope scope,
+ sparse_tensor::LoopOrderingStrategy strategy);
//===----------------------------------------------------------------------===//
// The PreSparsificationRewriting pass.
diff --git a/mlir/include/mlir/Dialect/SparseTensor/Transforms/Passes.td b/mlir/include/mlir/Dialect/SparseTensor/Transforms/Passes.td
index 2513e106f5b06..0b8562e484f51 100644
--- a/mlir/include/mlir/Dialect/SparseTensor/Transforms/Passes.td
+++ b/mlir/include/mlir/Dialect/SparseTensor/Transforms/Passes.td
@@ -81,6 +81,13 @@ def SparseReinterpretMap : Pass<"sparse-reinterpret-map", "ModuleOp"> {
clEnumValN(mlir::ReinterpretMapScope::kExceptGeneric,
"except-generic",
"Run on operations expect linalg.generic (e.g., foreach)"))}]>,
+ Option<"loopOrderingStrategy", "loop-ordering-strategy", "mlir::sparse_tensor::LoopOrderingStrategy",
+ "mlir::sparse_tensor::LoopOrderingStrategy::kDefault",
+ "Set the loop ordering strategy for sparse code generation", [{llvm::cl::values(
+ clEnumValN(mlir::sparse_tensor::LoopOrderingStrategy::kDefault, "default",
+ "Default strategy (eagerly selects last loop in topological sort)"),
+ clEnumValN(mlir::sparse_tensor::LoopOrderingStrategy::kDenseOuter, "dense-outer",
+ "Prefer dense, then compressed, then singleton dimensions outermost"))}]>,
];
}
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseReinterpretMap.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseReinterpretMap.cpp
index a1e35b87399ca..0fc5cc76de39c 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseReinterpretMap.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseReinterpretMap.cpp
@@ -59,7 +59,7 @@ struct DemapInsRewriter : public OpRewritePattern<SourceOp> {
// Flattens an affine expression into a list of AffineDimExprs.
struct AffineDimCollector : public AffineExprVisitor<AffineDimCollector> {
- explicit AffineDimCollector(unsigned dimNum) : dims(dimNum){};
+ explicit AffineDimCollector(unsigned dimNum) : dims(dimNum) {};
void visitDimExpr(AffineDimExpr expr) { dims.set(expr.getPosition()); }
BitVector dims;
};
@@ -67,7 +67,7 @@ struct AffineDimCollector : public AffineExprVisitor<AffineDimCollector> {
// Flattens an affine expression into a list of AffineDimExprs.
struct AffineExprAdmissibleVisitor
: public AffineExprVisitor<AffineExprAdmissibleVisitor> {
- explicit AffineExprAdmissibleVisitor(bool isOutput) : isOutput(isOutput){};
+ explicit AffineExprAdmissibleVisitor(bool isOutput) : isOutput(isOutput) {};
// We only allow AffineDimExpr on output.
void visitAddExpr(AffineBinaryOpExpr expr) {
@@ -407,7 +407,10 @@ struct GenericOpReinterpretMap
};
struct GenericOpScheduler : public OpRewritePattern<linalg::GenericOp> {
- using OpRewritePattern::OpRewritePattern;
+ GenericOpScheduler(MLIRContext *context,
+ sparse_tensor::LoopOrderingStrategy strategy)
+ : OpRewritePattern<linalg::GenericOp>(context), strategy(strategy) {}
+
LogicalResult matchAndRewrite(linalg::GenericOp linalgOp,
PatternRewriter &rewriter) const override {
if (linalgOp.getNumDpsInits() != 1 || !linalgOp.hasPureTensorSemantics() ||
@@ -420,7 +423,8 @@ struct GenericOpScheduler : public OpRewritePattern<linalg::GenericOp> {
if (linalgOp->hasAttr(sorted))
return failure();
- auto scheduler = IterationGraphSorter::fromGenericOp(linalgOp);
+ // Pass strategy to IterationGraphSorter.
+ auto scheduler = IterationGraphSorter::fromGenericOp(linalgOp, strategy);
bool isAdmissible = false;
AffineMap order;
// A const list of all masks that we used for iteration graph
@@ -582,6 +586,9 @@ struct GenericOpScheduler : public OpRewritePattern<linalg::GenericOp> {
// TODO: convert more than one?
return failure();
}
+
+private:
+ sparse_tensor::LoopOrderingStrategy strategy;
};
//===----------------------------------------------------------------------===//
@@ -786,12 +793,13 @@ struct ForeachOpDemapper
} // namespace
-void mlir::populateSparseReinterpretMap(RewritePatternSet &patterns,
- ReinterpretMapScope scope) {
+void mlir::populateSparseReinterpretMap(
+ RewritePatternSet &patterns, ReinterpretMapScope scope,
+ sparse_tensor::LoopOrderingStrategy strategy) {
if (scope == ReinterpretMapScope::kAll ||
scope == ReinterpretMapScope::kGenericOnly) {
- patterns.add<GenericOpReinterpretMap, GenericOpScheduler>(
- patterns.getContext());
+ patterns.add<GenericOpReinterpretMap>(patterns.getContext());
+ patterns.add<GenericOpScheduler>(patterns.getContext(), strategy);
}
if (scope == ReinterpretMapScope::kAll ||
scope == ReinterpretMapScope::kExceptGeneric) {
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorPasses.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorPasses.cpp
index 153b9b170e5d3..b660e22154688 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorPasses.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorPasses.cpp
@@ -67,12 +67,13 @@ struct SparseReinterpretMap
SparseReinterpretMap(const SparseReinterpretMap &pass) = default;
SparseReinterpretMap(const SparseReinterpretMapOptions &options) {
scope = options.scope;
+ loopOrderingStrategy = options.loopOrderingStrategy;
}
void runOnOperation() override {
auto *ctx = &getContext();
RewritePatternSet patterns(ctx);
- populateSparseReinterpretMap(patterns, scope);
+ populateSparseReinterpretMap(patterns, scope, loopOrderingStrategy);
(void)applyPatternsGreedily(getOperation(), std::move(patterns));
}
};
@@ -438,6 +439,14 @@ mlir::createSparseReinterpretMapPass(ReinterpretMapScope scope) {
return std::make_unique<SparseReinterpretMap>(options);
}
+std::unique_ptr<Pass> mlir::createSparseReinterpretMapPass(
+ ReinterpretMapScope scope, sparse_tensor::LoopOrderingStrategy strategy) {
+ SparseReinterpretMapOptions options;
+ options.scope = scope;
+ options.loopOrderingStrategy = strategy;
+ return std::make_unique<SparseReinterpretMap>(options);
+}
+
std::unique_ptr<Pass> mlir::createPreSparsificationRewritePass() {
return std::make_unique<PreSparsificationRewritePass>();
}
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/IterationGraphSorter.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/IterationGraphSorter.cpp
index c7e463a5a5b49..7ebe20e9674ce 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/IterationGraphSorter.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/IterationGraphSorter.cpp
@@ -80,6 +80,52 @@ inline static bool includesDenseOutput(SortMask mask) {
return includesAny(mask, SortMask::kIncludeDenseOutput);
}
+/// Returns a sparsity rank for loop ordering: lower values indicate
+/// dimensions that should be placed in outer loops.
+/// 0 = Dense, 1 = Compressed, 2 = Singleton, 3 = Other/Unknown
+static unsigned getLoopSparsityRank(unsigned loop, ArrayRef<Value> allTensors,
+ ArrayRef<AffineMap> allMaps) {
+ unsigned bestRank = 3; // Default: most sparse (unknown/singleton-like)
+
+ for (auto [tensor, map] : llvm::zip(allTensors, allMaps)) {
+ // Check if this loop accesses this tensor
+ bool loopAccessesTensor = false;
+ unsigned tensorDim = 0;
+ for (AffineExpr expr : map.getResults()) {
+ if (auto dimExpr = dyn_cast<AffineDimExpr>(expr)) {
+ if (dimExpr.getPosition() == loop) {
+ loopAccessesTensor = true;
+ break;
+ }
+ }
+ tensorDim++;
+ }
+
+ if (loopAccessesTensor) {
+ const auto enc = getSparseTensorEncoding(tensor.getType());
+ if (!enc) {
+ // Dense tensor - highest priority
+ return 0;
+ } else {
+ // Sparse tensor - check the level type for this dimension
+ auto lvlTypes = enc.getLvlTypes();
+ if (tensorDim < lvlTypes.size()) {
+ auto lvlType = lvlTypes[tensorDim];
+ if (isDenseLT(lvlType)) {
+ return 0; // Dense level
+ } else if (isCompressedLT(lvlType)) {
+ bestRank = std::min(bestRank, 1u); // Compressed level
+ } else if (isSingletonLT(lvlType)) {
+ bestRank = std::min(bestRank, 2u); // Singleton level
+ }
+ }
+ }
+ }
+ }
+
+ return bestRank;
+}
+
AffineMap IterationGraphSorter::topoSort() {
// The sorted result will put the first Reduction iterator to the
// latest possible position.
@@ -100,9 +146,40 @@ AffineMap IterationGraphSorter::topoSort() {
// We always prefer a parallel loop over a reduction loop because putting
// a reduction loop early might make the loop sequence inadmissible.
auto &it = !parIt.empty() ? parIt : redIt;
- auto src = it.back();
+
+ // Select loop based on strategy.
+ unsigned src;
+ switch (strategy) {
+ case sparse_tensor::LoopOrderingStrategy::kDefault:
+ src = it.back();
+ break;
+ case sparse_tensor::LoopOrderingStrategy::kDenseOuter: {
+ // Prefer dense, then compressed, then singleton dimensions outermost.
+ // Create combined tensor and map lists for analysis.
+ SmallVector<Value> allTensors = ins;
+ allTensors.push_back(out);
+ SmallVector<AffineMap> allMaps = loop2InsLvl;
+ allMaps.push_back(loop2OutLvl);
+
+ // Find loop with best (lowest) sparsity rank.
+ unsigned bestLoop = it[0];
+ unsigned bestRank = getLoopSparsityRank(bestLoop, allTensors, allMaps);
+
+ for (auto candidateLoop : it) {
+ unsigned rank = getLoopSparsityRank(candidateLoop, allTensors, allMaps);
+ if (rank < bestRank || (rank == bestRank && candidateLoop < bestLoop)) {
+ bestLoop = candidateLoop;
+ bestRank = rank;
+ }
+ }
+ src = bestLoop;
+ break;
+ }
+ }
+
loopOrder.push_back(src);
- it.pop_back();
+ // Remove the selected loop from the worklist.
+ it.erase(std::find(it.begin(), it.end(), src));
// Update in-degree, and push 0-degree node into worklist.
for (unsigned dst = 0; dst < numLoops; dst++) {
if (itGraph[src][dst] && --inDegree[dst] == 0) {
@@ -122,8 +199,8 @@ AffineMap IterationGraphSorter::topoSort() {
return AffineMap();
}
-IterationGraphSorter
-IterationGraphSorter::fromGenericOp(linalg::GenericOp genericOp) {
+IterationGraphSorter IterationGraphSorter::fromGenericOp(
+ linalg::GenericOp genericOp, sparse_tensor::LoopOrderingStrategy strategy) {
// Must be a demapped sparse kernel.
assert(!hasAnyNonIdentityOperandsOrResults(genericOp) &&
hasAnySparseOperandOrResult(genericOp) &&
@@ -140,14 +217,16 @@ IterationGraphSorter::fromGenericOp(linalg::GenericOp genericOp) {
genericOp.getIteratorTypesArray();
return IterationGraphSorter(std::move(ins), std::move(loopMap), out, outMap,
- std::move(iterTypes));
+ std::move(iterTypes), strategy);
}
IterationGraphSorter::IterationGraphSorter(
SmallVector<Value> &&ins, SmallVector<AffineMap> &&loop2InsLvl, Value out,
- AffineMap loop2OutLvl, SmallVector<utils::IteratorType> &&iterTypes)
+ AffineMap loop2OutLvl, SmallVector<utils::IteratorType> &&iterTypes,
+ sparse_tensor::LoopOrderingStrategy strategy)
: ins(std::move(ins)), loop2InsLvl(std::move(loop2InsLvl)), out(out),
- loop2OutLvl(loop2OutLvl), iterTypes(std::move(iterTypes)) {
+ loop2OutLvl(loop2OutLvl), iterTypes(std::move(iterTypes)),
+ strategy(strategy) {
// One map per tensor.
assert(loop2InsLvl.size() == ins.size());
// All the affine maps have the same number of dimensions (loops).
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/IterationGraphSorter.h b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/IterationGraphSorter.h
index a6abe9eb76c47..b2a16e9382758 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/IterationGraphSorter.h
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/IterationGraphSorter.h
@@ -13,6 +13,7 @@
#ifndef MLIR_DIALECT_SPARSETENSOR_TRANSFORMS_UTILS_ITERATIONGRAPHSORTER_H_
#define MLIR_DIALECT_SPARSETENSOR_TRANSFORMS_UTILS_ITERATIONGRAPHSORTER_H_
+#include "mlir/Dialect/SparseTensor/Transforms/Passes.h"
#include "mlir/IR/AffineMap.h"
namespace mlir {
@@ -41,9 +42,12 @@ enum class SortMask : unsigned {
class IterationGraphSorter {
public:
- /// Factory method that construct an iteration graph sorter
- /// for the given linalg.generic operation.
- static IterationGraphSorter fromGenericOp(linalg::GenericOp genericOp);
+ /// Factory method that constructs an iteration graph sorter
+ /// for the given linalg.generic operation with a specific loop ordering
+ /// strategy.
+ static IterationGraphSorter
+ fromGenericOp(linalg::GenericOp genericOp,
+ sparse_tensor::LoopOrderingStrategy strategy);
/// Returns a permutation that represents the scheduled loop order.
/// Note that the returned AffineMap could be null if the kernel
@@ -58,7 +62,9 @@ class IterationGraphSorter {
IterationGraphSorter(SmallVector<Value> &&ins,
SmallVector<AffineMap> &&loop2InsLvl, Value out,
AffineMap loop2OutLvl,
- SmallVector<utils::IteratorType> &&iterTypes);
+ SmallVector<utils::IteratorType> &&iterTypes,
+ sparse_tensor::LoopOrderingStrategy strategy =
+ sparse_tensor::LoopOrderingStrategy::kDefault);
// Adds all the constraints in the given loop to level map.
void addConstraints(Value t, AffineMap loop2LvlMap);
@@ -84,6 +90,9 @@ class IterationGraphSorter {
// InDegree used for topo sort.
std::vector<unsigned> inDegree;
+
+ // Loop ordering strategy.
+ sparse_tensor::LoopOrderingStrategy strategy;
};
} // namespace sparse_tensor
More information about the Mlir-commits
mailing list