batch\-reduce (full) in projects: llvm-project

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Searched +full:batch +full:- +full:reduce (Results 1 – 25 of 28) sorted by relevance

/llvm-project/mlir/include/mlir/Dialect/Linalg/IR/
H A D	LinalgInterfaces.h	`1 //===- LinalgInterface.h - Linalg operations interfaces -------- 44 SmallVector<unsigned, 2> batch; global() member 76 SmallVector<unsigned, 2> batch; global() member [all...]`
H A D	LinalgNamedStructuredOps.yaml	`3 --- !LinalgOpConfig 7 doc: \|- 13 - hasCanonicalizer 16 - !LinalgOperandDefConfig 20 shape_map: affine_map<() -> ()> 21 - !LinalgOperandDefConfig 25 shape_map: affine_map<() -> ()> 26 - !LinalgOperandDefConfi [all...]`
/llvm-project/mlir/include/mlir/Dialect/Vector/Transforms/
H A D	LoweringPatterns.h	`1 //===- LoweringPatterns.h - Vector rewrite patterns --------* [all...]`
/llvm-project/llvm/tools/llvm-reduce/deltas/
H A D	ReduceFunctions.cpp	1 //===- ReduceFunctions.cpp - Specialized Delta Pass -----------------------===// 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 7 //===----------------------------------------------------------------------===// 10 // to reduce functions (and any instruction that calls it) in the provided 13 //===----------------------------------------------------------------------===// 29 // Record all out-of-chunk functions. in extractFunctionsFromModule() 33 // reduce. Additionally, intrinsics may have additional operand in extractFunctionsFromModule() 44 // Then, drop body of each of them. We want to batch this and do nothing else in extractFunctionsFromModule() 47 F->dropAllReferences(); in extractFunctionsFromModule() 52 F->replaceAllUsesWith(getDefaultValue(F->getType())); in extractFunctionsFromModule() [all …]
/llvm-project/llvm/docs/
H A D	HowToAddABuilder.rst	28 commits from the llvm-zorg repository. 52 with the "config owner". We do expect "resource owners" - who are generally 53 the contact listed in a workers attributes - to proxy requests to the relevant 74 of parallelism (-j param) would give the fastest build. You can build 77 #. Install buildbot-worker (currently we are using buildbot version 2.8.4). 79 as ``pip3 install buildbot-worker==2.8.4``. 81 #. Create a designated user account, your buildbot-worker will be running under, 84 #. Choose the buildbot-worker root directory (all builds will be placed under 85 it), buildbot-worker access name and password the build master will be using 86 to authenticate your buildbot-worke [all...]
H A D	JITLink.rst	`11 This document aims to provide a high-level overview of the design and API 25 static constructors, eh-frame registration for exceptions, and TLV support for 26 thread locals; Swift and Objective-C require language runtime registration for 34 1. Cross-process and cross-architecture linking of single relocatable objects 57 ----- [all...]`
/llvm-project/mlir/lib/Dialect/Vector/Transforms/
H A D	LowerVectorContract.cpp	`1 //===- LowerVectorContract.cpp - Lower 'vector.contract' operation -------- [all...]`
/llvm-project/mlir/python/mlir/dialects/linalg/opdsl/ops/
H A D	core_named_ops.py	6 Batch = S.Batch variable 398 includes zero-point adjustments for the left and right operands of the 402 C[D.m, D.n] += (TypeFn.cast_signed(U, A[D.m, D.k]) - TypeFn.cast_signed(U, AZp)) * ( 403 TypeFn.cast_signed(U, B[D.k, D.n]) - TypeFn.cast_signed(U, BZp) 449 """Performs a matrix-matrix-transpose multiplication of two 4D inputs. 468 lhs=TensorDef(TV.LhsType, Batch, S.M, S.K, S.M0, S.K0), 469 rhs=TensorDef(TV.RhsType, Batch, S.N, S.K, S.N0, S.K0), 470 accum=TensorDef(TV.AccumType, Batch, 491 batch_mmt4d( lhs=TensorDef(TV.LhsType, Batch, S.M, S.K, S.M0, S.K0), rhs=TensorDef(TV.RhsType, Batch, S.N, S.K, S.N0, S.K0), accum=TensorDef(TV.AccumType, Batch, S.M, S.N, S.M0, S.N0, output=True), ) global() argument 512 batch_matmul( A=TensorDef(T1, Batch, S.M, S.K), B=TensorDef(T2, Batch, S.K, S.N), C=TensorDef(U, Batch, S.M, S.N, output=True), ) global() argument 530 batch_matmul_transpose_a( A=TensorDef(T1, Batch, S.K, S.M), B=TensorDef(T2, Batch, S.K, S.N), C=TensorDef(U, Batch, S.M, S.N, output=True), ) global() argument 549 batch_matmul_transpose_b( A=TensorDef(T1, Batch, S.M, S.K), B=TensorDef(T2, Batch, S.N, S.K), C=TensorDef(U, Batch, S.M, S.N, output=True), ) global() argument 568 quantized_batch_matmul( A=TensorDef(T1, Batch, S.M, S.K), B=TensorDef(T2, Batch, S.K, S.N), AZp=ScalarDef(I32), BZp=ScalarDef(I32), C=TensorDef(U, Batch, S.M, S.N, output=True), ) global() argument 589 batch_reduce_matmul( A=TensorDef(T1, Batch, S.M, S.K), B=TensorDef(T2, Batch, S.K, S.N), C=TensorDef(U, S.M, S.N, output=True), ) global() argument 636 batch_matvec( A=TensorDef(T1, Batch, S.M, S.K), B=TensorDef(T2, Batch, S.K), C=TensorDef(U, Batch, S.M, output=True), ) global() argument 654 batch_vecmat( A=TensorDef(T1, Batch, S.K), B=TensorDef(T2, Batch, S.K, S.N), C=TensorDef(U, Batch, S.N, output=True), ) global() argument [all...]
/llvm-project/clang-tools-extra/clangd/
H A D	Selection.cpp	1 //===--- Selection.cpp ----------------------------------------------------===// 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 7 //===----------------------------------------------------------------------===// 53 for (const auto N = Common; N; N = N->Parent) { in recordMetrics() 54 if (const auto RE = N->ASTNode.get<RecoveryExpr>()) { in recordMetrics() 56 RecoveryType.record(RE->isTypeDependent() ? 0 : 1, LanguageLabel); in recordMetrics() 71 // [----] MemberExpr, base = A().<anonymous>, member = b in getSourceRange() 72 // [----] MemberExpr: base = A(), member = <anonymous> in getSourceRange() 73 // [-] CXXConstructExpr in getSourceRange() 75 // so we reduce its range to match the CXXConstructExpr. in getSourceRange() [all …]
/llvm-project/mlir/lib/Dialect/Linalg/Transforms/
H A D	DropUnitDims.cpp	`1 //===- DropUnitDims.cpp - Pass to drop use of unit-extent for broadcasting ===// 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 7 //===--- [all...]`
/llvm-project/mlir/test/Conversion/TosaToLinalg/
H A D	tosa-to-linalg.mlir	`1 // RUN: mlir-opt --split-input-file -pass-pipeline="builtin.module(func.func(tosa-to-linalg))" %s -verif [all...]`
/llvm-project/llvm/test/Transforms/SLPVectorizer/RISCV/
H A D	reductions.ll	`2 ; RUN: opt < %s -passes=slp-vectorizer -mtriple=riscv64 \ 3 ; RUN: -mattr=+v,+zvfhmin,+zvfbfmin -riscv-v-slp-max-vf=0 - [all...]`
/llvm-project/clang-tools-extra/pseudo/lib/
H A D	GLR.cpp
/llvm-project/mlir/lib/Dialect/Tosa/IR/
H A D	TosaOps.cpp	`1 //===- TosaOps.cpp - MLIR Dialect for TOSA -------- [all...]`
/llvm-project/llvm/lib/Transforms/IPO/
H A D	Inliner.cpp	`1 //===- Inliner.cpp - Code common to all inliners -------- [all...]`
/llvm-project/clang/www/
H A D	features.html	1 <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN" 5 <META http-equiv="Content-Type" content="text/html; charset=ISO-8859-1"> 6 <title>Clang - Features and Goals</title> 14 <!--#include virtual="menu.html.incl"--> 18 <!--***********************************************************************--> 19 <h1>Clang - Features and Goals</h1> 20 <!--*********************************************************************--> 28 <p>End-User Features:</p> 48 <li><a href="#real">A real-world, production quality compiler</a></li> 56 <!--***********************************************************************--> [all …]
/llvm-project/llvm/test/CodeGen/X86/
H A D	atomic-unordered.ll	`2 ; RUN: llc -O0 < %s -mtriple=x86_64-linux-generic -verify-machineinstrs -mcpu=skylake \| FileCheck -… 3 ; RUN: llc -O3 < %s -mtriple=x86_64-linux-generic -verify-machineinstrs -mcpu=skylake \| FileCheck -… 6 ; CHECK-O0-LABEL: load_i8: 7 ; CHECK-O0: # %bb.0: 8 ; CHECK-O0-NEXT: movb (%rdi), %al 9 ; CHECK-O0-NEXT: retq 11 ; CHECK-O3-LABEL: load_i8: 12 ; CHECK-O3: # %bb.0: 13 ; CHECK-O3-NEXT: movzbl (%rdi), %eax 14 ; CHECK-O3-NEXT: retq [all …]`
/llvm-project/mlir/lib/Conversion/TosaToLinalg/
H A D	TosaToLinalg.cpp	`1 //===- TosaToLinalg.cpp - Lowering Tosa to Linalg Dialect -------- 1439 auto batch = inputTy.getDimSize(0); matchAndRewrite() local 1561 Value batch = b.create<linalg::IndexOp>(0); matchAndRewrite() local [all...]`
/llvm-project/llvm/lib/Analysis/
H A D	MemorySSA.cpp	`1 //===- MemorySSA.cpp - Memory SSA Builder -------- [all...]`
/llvm-project/mlir/docs/Rationale/
H A D	Rationale.md	5 decisions we made. This is not intended to be a "finely groomed" document - we 14 three-address SSA representations (like 19 high level dataflow graphs as well as target-specific code generated for high 24 MLIR stands for one of "Multi-Level IR" or "Multi-dimensional Loop IR" or 26 provides the rationale behind MLIR -- its actual 31 The Multi-Level Intermediate Representation (MLIR) is intended for easy 33 matrices of high dimensionality. It is thus well-suited to deep learning 35 sequential computation. The representation allows high-level optimization and 37 deep memory hierarchies --- general-purpose multicores, GPUs, and specialized 45 MLIR is a multi-level IR, i.e., it represents code at a domain-specific [all …]
/llvm-project/mlir/lib/Dialect/SparseTensor/IR/
H A D	SparseTensorDialect.cpp	`1 //===- SparseTensorDialect.cpp - Sparse tensor dialect implementation -----===// 5 // SPDX-License-Identifier: Apache-2. [all...]`
/llvm-project/compiler-rt/lib/scudo/standalone/
H A D	primary32.h	`1 //===-- primary32.h -------- [all...]`
H A D	primary64.h	`1 //===-- primary64.h -------- [all...]`
/llvm-project/mlir/include/mlir/Dialect/Linalg/Transforms/
H A D	Transforms.h	`1 //===- Transforms.h - Linalg transformations as patterns --------* [all...]`
/llvm-project/llvm/lib/Transforms/Scalar/
H A D	JumpThreading.cpp	`1 //===- JumpThreading.cpp - Thread control through conditional blocks ------===// 5 // SPDX-License-Identifie [all...]`