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/llvm-project-15.0.7/mlir/include/mlir/Dialect/Affine/
H A DLoopFusionUtils.h77 FusionStrategy(StrategyEnum strategy) : strategy(strategy) { in FusionStrategy() argument
78 assert(strategy != Sibling && in FusionStrategy()
84 FusionStrategy(Value memref) : strategy(Sibling), memref(memref) {} in FusionStrategy()
87 StrategyEnum getStrategy() const { return strategy; }; in getStrategy()
91 assert(strategy == Sibling && "Memref is only valid for sibling fusion"); in getSiblingFusionMemRef()
97 StrategyEnum strategy;
H A DUtils.h155 const VectorizationStrategy &strategy);
/llvm-project-15.0.7/mlir/lib/Dialect/Affine/Transforms/
H A DSuperVectorize.cpp631 strategy->loopToVectorDim[loop] = in vectorizeLoopIfProfitable()
761 const VectorizationStrategy *strategy = nullptr; member
1002 assert(state.strategy->vectorSizes.size() == 1 && in createMask()
1271 const VectorizationStrategy &strategy = *state.strategy; in vectorizeAffineForOp() local
1300 auto it = strategy.reductionLoops.find(forOp); in vectorizeAffineForOp()
1301 assert(it != strategy.reductionLoops.end() && in vectorizeAffineForOp()
1536 state.strategy = &strategy; in vectorizeLoopNest()
1690 VectorizationStrategy strategy; in vectorizeLoops() local
1693 strategy.reductionLoops = reductionLoops; in vectorizeLoops()
1699 &strategy); in vectorizeLoops()
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/llvm-project-15.0.7/mlir/include/mlir/Dialect/SparseTensor/Transforms/
H A DPasses.td66 Option<"parallelization", "parallelization-strategy", "int32_t", "0",
67 "Set the parallelization strategy">,
68 Option<"vectorization", "vectorization-strategy", "int32_t", "0",
69 "Set the vectorization strategy">,
120 Option<"sparseToSparse", "s2s-strategy", "int32_t", "0",
121 "Set the strategy for sparse-to-sparse conversion">,
/llvm-project-15.0.7/mlir/include/mlir/Dialect/Linalg/
H A DPasses.td176 : Pass<"linalg-strategy-tile-and-fuse-pass", "func::FuncOp"> {
188 : Pass<"linalg-strategy-tile-pass", "func::FuncOp"> {
201 : Pass<"linalg-strategy-pad-pass", "func::FuncOp"> {
214 : Pass<"linalg-strategy-generalize-pass", "func::FuncOp"> {
228 : Pass<"linalg-strategy-decompose-pass", "func::FuncOp"> {
239 : Pass<"linalg-strategy-interchange-pass", "func::FuncOp"> {
250 : Pass<"linalg-strategy-peel-pass", "func::FuncOp"> {
266 : Pass<"linalg-strategy-vectorize-pass", "func::FuncOp"> {
281 : Pass<"linalg-strategy-enable-pass", "func::FuncOp"> {
293 : Pass<"linalg-strategy-lower-vectors-pass", "func::FuncOp"> {
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/llvm-project-15.0.7/mlir/test/Dialect/SparseTensor/
H A Dsparse_parallel.mlir1 // RUN: mlir-opt %s -sparsification="parallelization-strategy=0" | \
3 // RUN: mlir-opt %s -sparsification="parallelization-strategy=1" | \
5 // RUN: mlir-opt %s -sparsification="parallelization-strategy=2" | \
7 // RUN: mlir-opt %s -sparsification="parallelization-strategy=3" | \
9 // RUN: mlir-opt %s -sparsification="parallelization-strategy=4" | \
/llvm-project-15.0.7/llvm/lib/Support/
H A DParallel.cpp20 llvm::ThreadPoolStrategy llvm::parallel::strategy; member in llvm::parallel
83 static void *call() { return new ThreadPoolExecutor(strategy); } in call()
186 if (NumItems > 1 && parallel::strategy.ThreadsRequested != 1) { in parallelFor()
/llvm-project-15.0.7/mlir/test/lib/Dialect/Affine/
H A DTestVectorizationUtils.cpp234 VectorizationStrategy strategy; in testVecAffineLoopNest() local
235 strategy.vectorSizes.push_back(4 /*vectorization factor*/); in testVecAffineLoopNest()
236 strategy.loopToVectorDim[outermostLoop] = 0; in testVecAffineLoopNest()
239 (void)vectorizeAffineLoopNest(loopsToVectorize, strategy); in testVecAffineLoopNest()
/llvm-project-15.0.7/llvm/docs/
H A DGarbageCollection.rst18 First, you should pick a collector strategy. LLVM includes a number of built
20 Note that the collector strategy is a description of how LLVM should generate
24 Next, mark your generated functions as using your chosen collector strategy.
61 your final stack maps. Depending on the collector strategy chosen, this is
201 IR features is specified by the selected :ref:`GC strategy description
366 Function's selected :ref:`GC strategy <plugin>`.
382 selected :ref:`GC strategy <plugin>`.
399 To use this collector strategy, mark your functions with:
492 a ``gcroot`` strategy.
531 Support for this GC strategy is a work in progress. This strategy will
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/llvm-project-15.0.7/clang-tools-extra/pseudo/
H A DDesignNotes.md54 - the recovery strategy knows whether we're recoverying last or not-last
55 - we could have the strategy return (pos, symbol parsed), and artificially
83 - when a node dies, we look up its recovery actions (symbol, strategy).
87 - we try each strategy: feeding in the start position = token of the dying node
/llvm-project-15.0.7/llvm/include/llvm/Support/
H A DParallel.h30 extern ThreadPoolStrategy strategy;
188 if (parallel::strategy.ThreadsRequested != 1) {
209 if (parallel::strategy.ThreadsRequested != 1) { in parallelTransformReduce()
/llvm-project-15.0.7/llvm/tools/llvm-symbolizer/
H A DCMakeLists.txt4 # targets as well. Currently, there is no support for such a build strategy.
/llvm-project-15.0.7/lld/Common/
H A DFilesystem.cpp77 if (parallel::strategy.ThreadsRequested == 1) in unlinkAsync()
/llvm-project-15.0.7/openmp/docs/remarks/
H A DOMP120.rst6 This optimization remark indicates that the execution strategy for the OpenMP
11 machine. This execution strategy is closer to how the threads are actually
/llvm-project-15.0.7/mlir/docs/Tools/
H A Dmlir-reduce.md18 it runs on the certain MLIR input. Afterwards, select your reduction strategy
25 to the tree traversal strategy. The different strategies may lead to different
/llvm-project-15.0.7/mlir/test/Integration/Dialect/SparseTensor/CPU/
H A Dsparse_filter_conv2d.mlir8 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \
H A Dsparse_quantized_matmul.mlir8 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \
H A Dsparse_sum.mlir10 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \
H A Dsparse_scale.mlir9 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \
H A Dsparse_out_simple.mlir10 // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \
H A Dsparse_conversion_sparse2sparse.mlir2 // RUN: mlir-opt %s --sparse-compiler="s2s-strategy=2" | \
/llvm-project-15.0.7/clang/lib/CodeGen/
H A DCGObjC.cpp1141 PropertyImplStrategy strategy(CGM, propImpl); in generateObjCGetterBody() local
1142 switch (strategy.getKind()) { in generateObjCGetterBody()
1145 if (strategy.getIvarSize().isZero()) in generateObjCGetterBody()
1201 args.add(RValue::get(Builder.getInt1(strategy.isAtomic())), in generateObjCGetterBody()
1229 emitStructGetterCall(*this, ivar, strategy.isAtomic(), in generateObjCGetterBody()
1230 strategy.hasStrongMember()); in generateObjCGetterBody()
1420 PropertyImplStrategy strategy(CGM, propImpl); in generateObjCSetterBody() local
1421 switch (strategy.getKind()) { in generateObjCSetterBody()
1424 if (strategy.getIvarSize().isZero()) in generateObjCSetterBody()
1461 strategy.isAtomic(), strategy.isCopy()); in generateObjCSetterBody()
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/llvm-project-15.0.7/llvm/test/Transforms/LoopStrengthReduce/X86/
H A Dlsr-filtering-scaledreg.ll22 ; Without filtering non-optimal formulae with the same ScaledReg and Scale, the strategy
/llvm-project-15.0.7/llvm/docs/HistoricalNotes/
H A D2001-05-19-ExceptionResponse.txt27 other one is needed on demand. Also this strategy fits with the "zero
/llvm-project-15.0.7/libc/docs/
H A Dredirectors.rst11 system libc itself. In this document, we present a strategy one can employ to

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