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现代体系结构的优化编译器(带封面+英文版+文字可复制)

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Optimizing compilers for modern architectures: a dependence based approach

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Chapter Draft of February 8, 2001

CHAPTER 1

Compiler Challenges for High-Performance Architectures

1.1

Overview and Goals

1.2

Pipelining

1.2.1 Pipelined Instruction Units 21

1.2.2 Pipelined Execution Units 23

1.2.3 Parallel Functional Units 24

1.2.4 Compiling for Scalar Pipelines. 25

1.3

Vector Instructions

1.3.1 Vector Hardware Overview 29

1.3.2 Compiling for Vector Pipelines 30

1.4

Superscalar and VLIW Processors

1.4.1 Multiple-Issue Instruction Units 32

1.4.2 Compiling for Multiple-Issue Processors 33

1.5

Processor Parallelism

1.5.1 Compiling for Asynchronous Parallelism 37

1.6

Memory Hierarchy

1.6.1 Compiling for Memory Hierarchy 41

1.7

A Case Study: Matrix Multiplication

1.8

Advanced Compiler Technology

1.8.1 Dependence 48

1.8.2 Transformations 50

1.9

Chapter Summary

1.10

Case Studies

1.11

Historical Comments and References

1.12

Exercises

1.13

References

CHAPTER 2

Dependence: Theory and Practice

2.1

Introduction

2.2

Dependence and its Properties

2.2.1 Load-Store Classiﬁcation 60

2.2.2 Dependence in Loops 61

2.2.3 Dependence and Transformations 63

2.2.4 Distance and Direction Vectors 68

2.2.5 Loop-carried and Loop-independent Dependences 72

2.2.5.1 Loop-Carried Dependence 72

2.2.5.2 Loop-Independent Dependences 76

2.2.5.3 Iteration Reordering 78

ADVANCED COMPILING FOR HIGH PERFORMANCE

2.3

Simple Dependence Testing

2.4

Parallelization and Vectorization

2.4.1 Parallelization 82

2.4.2 Vectorization 83

2.4.3 An Advanced Vectorization Algorithm 86

2.5

Chapter Summary

2.6

Case Studies

2.7

Historical Comments and References

2.8

Exercises

2.9

References

CHAPTER 3

Dependence Testing

3.1

Introduction

3.1.1 Background and Terminology 101

3.1.1.1 Indexes and Subscripts 101

3.1.1.2 Nonlinearity 101

3.1.1.3 Conservative Testing 102

3.1.1.4 Complexity 103

3.1.1.5 Separability 103

3.1.1.6 Coupled Subscript Groups 104

3.2

Dependence Testing Overview

106

3.2.1 Subscript Partitioning 106

3.2.2 Merging Direction Vectors 107

3.3

Single-Subscript Dependence Tests

108

3.3.1 ZIV Test 108

3.3.2 SIV Tests 108

3.3.2.1 Strong SIV Subscripts 109

3.3.2.2 Weak SIV Subscripts 110

3.3.2.3 Weak-zero SIV Subscripts 111

3.3.2.4 Weak-crossing SIV Subscripts 112

3.3.2.5 Complex Iteration Spaces 114

3.3.2.6 Symbolic SIV Dependence Tests 117

3.3.2.7 Breaking Conditions 119

3.3.2.8 An Exact SIV Test 121

3.3.3 Multiple Induction Variable Tests 122

3.3.3.1 GCD Test 124

3.3.3.2 Banerjee Inequality 124

3.3.3.3 Handling Symbolics in the Banerjee Inequality 130

3.3.3.4 Trapezoidal Banerjee Inequality 131

3.3.3.5 Testing for All Direction Vectors 139

3.4

Testing in Coupled Groups

140

Chapter Draft of February 8, 2001

3.4.1 The Delta Test 141

3.4.1.1 Constraints 143

3.4.1.2 Intersecting Constraints 144

3.4.1.3 Constraint Propagation 145

3.4.1.4 Precision and Complexity 149

3.4.2 More Powerful Multiple-Subscript Tests 150

3.5

An Empirical Study

151

3.6

Putting It All Together

154

3.7

Chapter Summary

160

3.8

Case Studies

162

3.9

Historical Comments and References

163

3.10

Exercises

164

3.11

References

165

CHAPTER 4

Preliminary Transformations

169

4.1

Introduction

169

4.2

Information Requirements

172

4.3

Loop Normalization

173

4.4

Data Flow Analysis

176

4.4.1 Deﬁnition-Use Chains 176

4.4.2 Dead Code Elimination 180

4.4.3 Constant Propagation 181

4.4.4 Static Single-Assignment Form 184

4.5

Induction-Variable Exposure

192

4.5.1 Forward Expression Substitution 192

4.5.2 Induction-Variable Substitution 196

4.5.3 Driving the Substitution Process 200

4.6

Chapter Summary

204

4.7

Case Studies

204

4.8

Historical Comments and References

206

4.9

Exercises

207

4.10

References

208

CHAPTER 5

Enhancing Fine-Grained Parallelism

211

5.1

Overview

211

5.2

Loop Interchange

213

ADVANCED COMPILING FOR HIGH PERFORMANCE

5.2.1 Safety of Loop Interchange 214

5.2.2 Proﬁtability of Loop Interchange 218

5.2.3 Loop Interchange and Vectorization 219

5.2.3.1 A Code Generation Framework 223

5.2.3.2 General Loop Selection and Interchange 223

5.3

Scalar Expansion

226

5.4

Scalar and Array Renaming

236

5.5

Node Splitting

244

5.6

Recognition of Reductions

247

5.7

Index-set Splitting

251

5.7.1 Threshold Analysis 251

5.7.2 Loop Peeling 253

5.7.3 Section-based Splitting 254

5.8

Run-time Symbolic Resolution

256

5.9

Loop Skewing

258

5.10

Putting It All Together

263

5.11

Complications of Real Machines

270

5.12

Chapter Summary

274

5.13

Case Studies

275

5.14

Historical Comments and References

280

5.15

Exercises

281

5.16

References

282

CHAPTER 6

Creating Coarse-Grained Parallelism

285

6.1

Introduction

285

6.2

Single-Loop Methods

287

6.2.1 Privatization 287

6.2.2 Loop Distribution 292

6.2.3 Alignment 293

6.2.4 Code Replication 297

6.2.5 Loop Fusion 302

6.2.5.1 Typed Fusion 308

6.2.5.2 Unordered and Ordered Typed Fusion 316

6.2.5.3 Cohort Fusion 318

6.3

Perfect Loop Nests

320

6.3.1 Loop Interchange 320

6.3.2 Loop Selection 325

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Optimizing Compilers for Modern Architectures

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Optimizing Compilers for Modern Architectures_A_Dependence-based_Approach

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