编译原理 技术与工具 第2版PDF电子书下载

1 Introduction 1

1.1 Language Processors 1

1.1.1 Exercises for Section 1.1 3

1.2 The Structure of a Compiler 4

1.2.1 Lexical Analysis 5

1.2.2 Syntax Analysis 8

1.2.3 Semantic Analysis 8

1.2.4 Intermediate Code Generation 9

1.2.5 Code Optimization 10

1.2.6 Code Generation 10

1.2.7 Symbol-Table Management 11

1.2.8 The Grouping of Phases into Passes 11

1.2.9 Compiler-Construction Tools 12

1.3 The Evolution of Programming Languages 12

1.3.1 The Move to Higher-level Languages 13

1.3.2 Impacts on Compilers 14

1.3.3 Exercises for Section 1.3 14

1.4 The Science of Building a Compiler 15

1.4.1 Modeling in Compiler Design and Implementation 15

1.4.2 The Science of Code Optimization 15

1.5 Applications of Compiler Technology 17

1.5.1 Implementation of High-Level Programming Languages 17

1.5.2 Optimizations for Computer Architectures 19

1.5.3 Design of New Computer Architectures 21

1.5.4 Program Translations 22

1.5.5 Software Productivity Tools 23

1.6 Programming Language Basics 25

1.6.1 The Static/Dynamic Distinction 25

1.6.2 Environments and States 26

1.6.3 Static Scope and Block Structure 28

1.6.4 Explicit Access Control 31

1.6.5 Dynamic Scope 31

1.6.6 Parameter Passing Mechanisms 33

1.6.7 Aliasing 35

1.6.8 Exercises for Section 1.6 35

1.7 Summary of CHAPTER1 36

1.8 References for CHAPTER1 38

2 A Simple Syntax-Directed Translator 39

2.1 Introduction 40

2.2 Syntax Definition 42

2.2.1 Definition of Grammars 42

2.2.2 Derivations 44

2.2.3 Parse Trees 45

2.2.4 Ambiguity 47

2.2.5 Associativity of Operators 48

2.2.6 Precedence of Operators 48

2.2.7 Exercises for Section 2.2 51

2.3 Syntax-Directed Translation 52

2.3.1 Postfix Notation 53

2.3.2 Synthesized Attributes 54

2.3.3 Simple Syntax-Directed Definitions 56

2.3.4 Tree Traversals 56

2.3.5 Translation Schemes 57

2.3.6 Exercises for Section 2.3 60

2.4 Parsing 60

2.4.1 Top-Down Parsing 61

2.4.2 Predictive Parsing 64

2.4.3 When to Use e-Productions 65

2.4.4 Designing a Predictive Parser 66

2.4.5 Left Recursion 67

2.4.6 Exercises for Section 2.4 68

2.5 A Translator for Simple Expressions 68

2.5.1 Abstract anid Concrete Syntax 69

2.5.2 Adapting the Translation Scheme 70

2.5.3 Procedures for the Nonterminals 72

2.5.4 Simplifying the Translator 73

2.5.5 The Complete Program 74

2.6 Lexical Analysis 76

2.6.1 Removal of White Space and Comments 77

2.6.2 Reading Ahead 78

2.6.3 Constants 78

2.6.4 Recognizing Keywords and Identifiers 79

2.6.5 A Lexical Analyzer 81

2.6.6 Exercises for Section 2.6 84

2.7 Symbol Tables 85

2.7.1 Symbol Table Per Scope 86

2.7.2 The Use of SymbolTables 89

2.8 Intermediate Code Generation 91

2.8.1 Two Kinds of Intermediate Representations 91

2.8.2 Construction of Syntax Trees 92

2.8.3 Static Checking 97

2.8.4 Three-Address Code 99

2.8.5 Exercises for Section 2.8 105

2.9 Summary of CHAPTER2 105

3 Lexical Analysis 109

3.1 The Role of the Lexical Analyzer 109

3.1.1 Lexical Analysis Versus Parsing 110

3.1.2 Tokens， Patterns， and Lexemes 111

3.1.3 Attributes for Tokens 112

3.1.4 Lexical Errors 113

3.1.5 Exercises for Section 3.1 114

3.2 Input Buffering 115

3.2.1 Buffer Pairs 115

3.2.2 Sentinels 116

3.3 Specification of Tokens 116

3.3.1 Strings and Languages 117

3.3.2 Operations on Languages 119

3.3.3 Regular Expressions 120

3.3.4 Regular Definitions 123

3.3.5 Extensions of Regular Expressions 124

3.3.6 Exercises for Section 3.3 125

3.4 Recognition of Tokens 128

3.4.1 Transition Diagrams 130

3.4.2 Recognition of Reserved Words and Identifiers 132

3.4.3 Completion of the Running Example 133

3.4.4 Architecture of a Transition-Diagram-Based Lexical An-alyzer 134

3.4.5 Exercises for Section 3.4 136

3.5 The Lexical-Analyzer Generator Lex 140

3.5.1 Use of Lex 140

3.5.2 Structure of Lex Programs 141

3.5.3 Conflict Resolution in Lex 144

3.5.4 The Lookahead Operator 144

3.5.5 Exercises for Section 3.5 146

3.6 Finite Automata 147

3.6.1 Nondeterministic Finite Automata 147

3.6.2 Transition Tables 148

3.6.3 Acceptance of Input Strings by Automata 149

3.6.4 Deterministic Finite Automata 149

3.6.5 Exercises for Section 3.6 151

3.7 From Regular Expressions to Automata 152

3.7.1 Conversion of an NFA to a DFA 152

3.7.2 Simulation of an NFA 156

3.7.3 Efficiency of NFA Simulation 157

3.7.4 Construction of an NFA from a Regular Expression 159

3.7.5 Efficiency of String-Processing Algorithms 163

3.7.6 Exercises for Section 3.7 166

3.8 Design of a Lexical-Analyzer Generator 166

3.8.1 The Structure of the Generated Analyzer 167

3.8.2 Pattern Matching Based on NFA’s 168

3.8.3 DFA’s for Lexical Analyzers 170

3.8.4 Implementing the Lookahead Operator 171

3.8.5 Exercises for Section 3.8 172

3.9 Optimization of DFA-Based Pattern Matchers 173

3.9.1 Important States of an NFA 173

3.9.2 Functions Computed From the Syntax Tree 175

3.9.3 Computing nullable， firstpos， and lastpos 176

3.9.4 Computing followpos 177

3.9.5 Converting a Regular Expression Directly to a DFA 179

3.9.6 Minimizing the Number of States of a DFA 180

3.9.7 State Minimization in Lexical Analyzers 184

3.9.8 Trading Time for Space in DFA Simulation 185

3.9.9 Exercises for Section 3.9 186

3.10 Summary of CHAPTER3 187

3.11 References for CHAPTER3 189

4 Syntax Analysis 191

4.1 Introduction 192

4.1.1 The Role of the Parser 192

4.1.2 Representative Grammars 193

4.1.3 Syntax Error Handling 194

4.1.4 Error-Recovery Strategies 195

4.2 Context-Free Grammars 197

4.2.1 The Formal Definition of a Context-Freo Grammar 197

4.2.2 Notational Conventions 198

4.2.3 Derivations 199

4.2.4 Parse Trees and Derivations 201

4.2.5 Ambiguity 203

4.2.6 Verifying the Language Generated by a Grammar 204

4.2.7 Context-Free Grammars Versus Regular Expressions 205

4.2.8 Exercises for Section 4.2 206

4.3 Writing a Grammar 209

4.3.1 Lexical Versus Syntactic Analysis 209

4.3.2 Eliminating Ambiguity 210

4.3.3 Elimination of Left Recursion 212

4.3.4 Left Factoring 214

4.3.5 Non-Context-Free Language Constructs 215

4.3.6 Exercises for Section 4.3 216

4.4 Top-Down Parsing 217

4.4.1 Recursive-Descent Parsing 219

4.4.2 FIRST and FOLLOW 220

4.4.3 LL（1） Grammars 222

4.4.4 Nonrecursive Predictive Parsing 226

4.4.5 Error Recovery in Predictive Parsing 228

4.4.6 Exercises for Section 4.4 231

4.5 Bottom-Up Parsing 233

4.5.1 Reductions 234

4.5.2 Handle Pruning 235

4.5.3 Shift-Reduce Parsing 236

4.5.4 Conflicts During Shift-Reduce Parsing 238

4.5.5 Exercises for Section 4.5 240

4.6 Introduction to LR Parsing Simple LR 241

4.6.1 Why LR Parsers？ 241

4.6.2 Items and the LR（0） Automaton 242

4.6.3 The LR-Parsing Algorithm 248

4.6.4 Constructing SLR-Parsing Tables 252

4.6.5 Viable Prefixes 256

4.6.6 Exercises for Section 4.6 257

4.7 More Powerful LR Parsers 259

4.7.1 Canonical LR（1）Items 260

4.7.2 Constructing LR（1） Sets of Items 261

4.7.3 Canonical LR（1） Parsing Tables 265

4.7.4 Constructing LALR Parsing Tables 266

4.7.5 Efficient Construction of LALR Parsing Tables 270

4.7.6 Compaction of LR Parsing Tables 275

4.7.7 Exercises for Section 4.7 277

4.8 Using Ambiguous Grammars 278

4.8.1 Precedence and Associativity to Resolve Conflicts 279

4.8.2 The “Dangling-Else” Ambiguity 281

4.8.3 Error Recovery in LR Parsing 283

4.8.4 Exercises for Section 4.8 285

4.9 Parser Generators 287

4.9.1 The Parser Generator Yacc 287

4.9.2 Using Yacc with Ambiguous Grammars 291

4.9.3 Creating Yacc Lexical Analyzers with Lex 294

4.9.4 Error Recovery in Yacc 295

4.9.5 Exercises for Section 4.9 297

4.10 Summary of CHAPTER4 297

4.11 References for CHAPTER4 300

5 Syntax-Directed Translation 303

5.1 Syntax-Directed Definitions 304

5.1.1 Inherited and Synthesized Attributes 304

5.1.2 Evaluating an SDD at the Nodes of a Parse Tree 306

5.1.3 Exercises for Section 5.1 309

5.2 Evaluation Orders for SDD’s 310

5.2.1 Dependency Graphs 310

5.2.2 Ordering the Evaluation of Attributes 312

5.2.3 S-Attributed Definitions 312

5.2.4 L-Attributed Definitions 313

5.2.5 Semantic Rules with Controlled Side Effects 314

5.2.6 Exercises for Section 5.2 317

5.3 Applications of Syntax-Directed Translation 318

5.3.1 Construction of Syntax Trees 318

5.3.2 The Structure of a Type 321

5.3.3 Exercises for Section 5.3 323

5.4 Syntax-Directed Translation Schemes 324

5.4.1 Postfix Translation Schemes 324

5.4.2 Parser-Stack Implementation of Postfix SDT’s 325

5.4.3 SDT’s With Actions Inside Productions 327

5.4.4 Eliminating Left Recursion From SDT’s 328

5.4.5 SDT’s for L-Attributed Definitions 331

5.4.6 Exercises for Section 5.4 336

5.5 Implementing L-Attributed SDD’s 337

5.5.1 Translation During Recursive-Descent Parsing 338

5.5.2 On-The-Fly Code Generation 340

5.5.3 L-Attributed SDD’s and LL Parsing 343

5.5.4 Bottom-Up Parsing of L-Attributed SDD’s 348

5.5.5 Exercises for Section 5.5 352

5.6 Summary of CHAPTER5 353

5.7 References for CHAPTER5 354

6 Intermediate-Code Generation 357

6.1 Variants of Syntax Trees 358

6.1.1 Directed Acyclic Graphs for Expressions 359

6.1.2 The Value-Number Method for Constructing DAG’s 360

6.1.3 Exercises for Section 6.1 362

6.2 Three-Address Code 363

6.2.1 Addresses and Instructions 364

6.2.2 Quadruples 366

6.2.3 Triples 367

6.2.4 Static Single-Assignment Form 369

6.2.5 Exercises for Section 6.2 370

6.3 Types and Declarations 370

6.3.1 Type Expressions 371

6.3.2 Type Equivalence 372

6.3.3 Declarations 373

6.3.4 Storage Layout for Local Names 373

6.3.5 Sequences of Declarations 376

6.3.6 Fields in Records and Classes 376

6.3.7 Exercises for Section 6.3 378

6.4 Translation of Expressions 378

6.4.1 Operations Within Expressions 378

6.4.2 Incremental Translation 380

6.4.3 Addressing Array Elements 381

6.4.4 Translation of Array Referehces 383

6.4.5 Exercises for Section 6.4 384

6.5 Type Checking 386

6.5.1 Rules for Type Checking 387

6.5.2 Type Conversions 388

6.5.3 Overloading of Functions and Operators 390

6.5.4 Type Inference and Polymorphic Functions 391

6.5.5 An Algorithm for Unification 395

6.5.6 Exercises for Section 6.5 398

6.6 Control Flow 399

6.6.1 Boolean Expressions 399

6.6.2 Short-Circuit Code 400

6.6.3 Flow-of-Control Statements 401

6.6.4 Control-Flow Translation of Boolean Expressions 403

6.6.5 Avoiding Redundant Gotos 405

6.6.6 Boolean Values and Jumping Code 408

6.6.7 Exercises for Section 6.6 408

6.7 Backpatching 410

6.7.1 One-Pass Code Generation Using Backpatching 410

6.7.2 Backpatching for Boolean Expressions 411

6.7.3 Flow-of-Control Statements 413

6.7.4 Break-， Continue-， and Goto-Statements 416

6.7.5 Exercises for Section 6.7 417

6.8 Switch-Statements 418

6.8.1 Translation of Switch-Statements 419

6.8.2 Syntax-Directed Translation of SwitchStatements 420

6.8.3 Exercises for Section 6.8 421

6.9 Intermediate Code for Procedures 422

6.10 Summary of CHAPTER6 424

6.11 References for CHAPTER6 425

7 Run-Time Environments 427

7.1 Storage Organization 427

7.1.1 Static Versus Dynamic Storage Allocation 429

7.2 Stack Allocation of Space 430

7.2.1 Activation Trees 430

7.2.2 Activation Records 433

7.2.3 Calling Sequences 436

7.2.4 Variable-Length Data on the Stack 438

7.2.5 Exercises for Section 7.2 440

7.3 Access to Nonlocal Data on the Stack 441

7.3.1 Data Access Without Nested Procedures 442

7.3.2 Issues With Nested Procedures 442

7.3.3 A Language With Nested Procedure Declarations 443

7.3.4 Nesting Depth 443

7.3.5 Access Links 445

7.3.6 Manipulating Access Links 447

7.3.7 Access Links for Procedure Parameters 448

7.3.8 Displays 449

7.3.9 Exercises for Section 7.3 451

7.4 Heap Management 452

7.4.1 The Memory Manager 453

7.4.2 The Memory Hierarchy of a Computer 454

7.4.3 Locality in Programs 455

7.4.4 Reducing Fragmentation 457

7.4.5 Manual Deallocation Requests 460

7.4.6 Exercises for Section 7.4 463

7.5 Introduction to Garbage Collection 463

7.5.1 Design Goals for Garbage Collectors 464

7.5.2 Reachability 466

7.5.3 Reference Counting Garbage Collectors 468

7.5.4 Exercises forSection 7.5 470

7.6 Introduction to Trace-Based Collection 470

7.6.1 ABasic Mark-and-Sweep Collector 471

7.6.2 Basic Abstraction 473

7.6.3 Optimizing Mark-and-Sweep 475

7.6.4 Mark-and-Compact Garbage Collectors 476

7.6.5 Copying collectors 478

7.6.6 Comparing Costs 482

7.6.7 Exercises for Section 7.6 482

7.7 Short-Pause Garbage Collection 483

7.7.1 Incremental Garbage Collection 483

7.7.2 Incremental Reachability Analysis 485

7.7.3 Partial-Collection Basics 487

7.7.4 Generational Garbage Collection 488

7.7.5 The Train Algorithm 490

7.7.6 Exercises for Section 7.7 493

7.8 Advanced Topics in Garbage Collection 494

7.8.1 Parallel and Concurrent Garbage Collection 495

7.8.2 Partial Object Relocation 497

7.8.3 Conservative Collection for Unsafe Languages 498

7.8.4 Weak References 498

7.8.5 Exercises for Section 7.8 499

7.9 Summary of CHAPTER7 500

7.10 References for CHAPTER7 502

8 Code Generation 505

8.1 Issues in the Design of a Code Generator 506

8.1.1 Input to the Code Generator 507

8.1.2 The Target Program 507

8.1.3 Instruction Selection 508

8.1.4 Register Allocation 510

8.1.5 Evaluation Order 511

8.2 The Target Language 512

8.2.1 A Simple Target Machine Model 512

8.2.2 Program and Instruction Costs 515

8.2.3 Exercises for Section 8.2 516

8.3 Addresses in the Target Code 518

8.3.1 Static Allocation 518

8.3.2 Stack Allocation 520

8.3.3 Run-Time Addresses for Names 522

8.3.4 Exercises for Section 8.3 524

8.4 Basic Blocks and Flow Graphs 525

8.4.1 Basic Blocks 526

8.4.2 Next-Use Information 528

8.4.3 Flow Graphs 529

8.4.4 Representation of Flow Graphs 530

8.4.5 Loops 531

8.4.6 Exercises for Section 8.4 531

8.5 Optimization of Basic Blocks 533

8.5.1 The DAG Representation of Basic Blocks 533

8.5.2 Finding Local Common Subexpressions 534

8.5.3 Dead Code Elimination 535

8.5.4 The Use of Algebraic Identities 536

8.5.5 Representation of Array References 537

8.5.6 Pointer Assignments and Procedure Calls 539

8.5.7 Reassembling Basic Blocks From DAG’s 539

8.5.8 Exercises for Section 8.5 541

8.6 A Simple Code Generator 542

8.6.1 Register and Address Descriptors 543

8.6.2 The Code-Generation Algorithm 544

8.6.3 Design of the Function getReg 547

8.6.4 Exercises for Section 8.6 548

8.7 Peephole Optimization 549

8.7.1 Eliminating Redundant Loads and Stores 550

8.7.2 Eliminating Unreachable Code 550

8.7.3 Flow-of-Control Optimizations 551

8.7.4 Algebraic Simplification and Reduction in Strength 552

8.7.5 Use of Machine Idioms 552

8.7.6 Exercises for Section 8.7 553

8.8 Register Allocation and Assignment 553

8.8.1 Global Register Allocation 553

8.8.2 Usage Counts 554

8.8.3 Register Assignment for Outer Loops 556

8.8.4 Register Allocation by Graph Coloring 556

8.8.5 Exercises for Section 8.8 557

8.9 Instruction Selection by Tree Rewriting 558

8.9.1 Tree-Translation Schemes 558

8.9.2 Code Generation by Tiling an InputTree 560

8.9.3 Pattern Matching by Parsing 563

8.9.4 Routines for Semantic Checking 565

8.9.5 General Tree Matching 565

8.9.6 Exercises for Section 8.9 567

8.10 Optimal Code Generation for Expressions 567

8.10.1 Ershov Numbers 567

8.10.2 Generating Code From Labeled Expression Trees 568

8.10.3 Evaluating Expressions with an Insufficient Supply of Reg-isters 570

8.10.4 Exercises for Section 8.10 572

8.11 Dynamic Programming Code-Generation 573

8.11.1 Contiguous Evaluation 574

8.11.2 The Dynamic Programming Algorithm 575

8.11.3 Exercises for Section 8.11 577

8.12 Summary of CHAPTER8 578

8.13 References for CHAPTER8 579

9 Machine-Independent Optimizations 583

9.1 The Principal Sources of Optimization 584

9.1.1 Causes of Redundancy 584

9.1.2 A Running Example Quicksort 585

9.1.3 Semantics-Preserving Transformations 586

9.1.4 Global Common Subexpressions 588

9.1.5 Copy Propagation 590

9.1.6 Dead-Code Elimination 591

9.1.7 Code Motion 592

9.1.8 Induction Variables and Reduction in Strength 592

9.1.9 Exercises for Section 9.1 596

9.2 Introduction to Data-Flow Analysis 597

9.2.1 The Data-Flow Abstraction 597

9.2.2 The Data-Flow Analysis Schema 599

9.2.3 Data-Flow Schemas on Basic Blocks 600

9.2.4 Reaching Definitions 601

9.2.5 Live-Variable Analysis 608

9.2.6 Available Expressions 610

9.2.7 Summary 614

9.2.8 Exercises for Section 9.2 615

9.3 Foundations of Data-Flow Analysis 618

9.3.1 Semilattices 618

9.3.2 Transfer Functions 623

9.3.3 The Iterative Algorithm for General Frameworks 626

9.3.4 Meaning of a Data-Flow Solution 628

9.3.5 Exercises for Section 9.3 631

9.4 Constant Propagation 632

9.4.1 Data-Flow Values for the Constant-Propagation Frame-work 633

9.4.2 The Meet for the Constant-Propagation Framework 633

9.4.3 Transfer Functions for the Constant-Propagation Frame-work 634

9.4.4 Monotonicity of the Constant-Propagation Framework 635

9.4.5 Nondistributivity of the Constant-Propagation Framework 635

9.4.6 Interpretation of the Results 637

9.4.7 Exercises for Section 9.4 637

9.5 Partial-Redundancy Elimination 639

9.5.1 The Sources of Redundancy 639

9.5.2 Can All Redundancy Be Eliminated？ 642

9.5.3 The Lazy-Code-Motion Problem 644

9.5.4 Anticipation of Expressions 645

9.5.5 The Lazy-Code-Motion Algorithm 646

9.5.6 Exercises for Section 9.5 655

9.6 Loops in Flow Graphs 655

9.6.1 Dominators 656

9.6.2 Depth-First Ordering 660

9.6.3 Edges in a Depth-First Spanning Tree 661

9.6.4 Back Edges and Reducibility 662

9.6.5 Depth of a Flow Graph 665

9.6.6 Natural Loops 665

9.6.7 Speed of Convergence of Iterative Data-Flow Algorithms 667

9.6.8 Exercises for Section 9.6 669

9.7 Region-Based Analysis 672

9.7.1 Regions 672

9.7.2 Region Hierarchies for Reducible Flow Graphs 673

9.7.3 Overview of a Region-Based Analysis 676

9.7.4 Necessary Assumptions About Transfer Functions 678

9.7.5 An Algorithm for Region-Based Analysis 680

9.7.6 Handling NonreducibleFlow Graphs 684

9.7.7 Exercises for Section 9.7 686

9.8 Symbolic Analysis 686

9.8.1 Affine Expressions of Reference Variables 687

9.8.2 Data-Flow Problem Formulation 689

9.8.3 Region-Based Symbolic Analysis 694

9.8.4 Exercises for Section9.8 699

9.9 Summary of CHAPTER9 700

9.10 References for CHAPTER9 703

10 Instruction-Level， Parallelism 707

10.1 Processor Architectures 708

10.1.1 Instruction Pipelines and Branch Delays 708

10.1.2 Pipelined Execution 709

10.1.3 Multiple Instruction Issue 710

10.2 Code-Scheduling Constraints 710

10.2.1 Data Dependence 711

10.2.2 FindingDependences Among Memory Accesses 712

10.2.3 Tradeoff Between Register Usage and Parallelism 713

10.2.4 Phase Ordering Between Register Allocation and CodeScheduling 716

10.2.5 Control Dependence 716

10.2.6 Speculative Execution Support 717

10.2.7 A Basic Machine Model 719

10.2.8 Exercises for Section 10.2 720

10.3 Basic-Block Scheduling 721

10.3.1 Data-Dependence Graphs 722

10.3.2 List Scheduling of Basic Blocks 723

10.3.3 Prioritized Topological Orders 725

10.3.4 Exercises for Section 10.3 726

10.4 Global Code Scheduling 727

10.4.1 Primitive Code Motion 728

10.4.2 Upward Code Motion 730

10.4.3 Downward Code Motion 731

10.4.4 Updating Data Dependences 732

10.4.5 Global Scheduling Algorithms 732

10.4.6 Advanced Code Motion Techniques 736

10.4.7 Interaction with Dynamic Schedulers 737

10.4.8 Exercises for Section 10.4 737

10.5 Software Pipelining 738

10.5.1 Introduction 738

10.5.2 Software Pipelining of Loops 740

10.5.3 Register Allocation and Code Generation 743

10.5.4 Do-Across Loops 743

10.5.5 Goals and Constraints of Software Pipelining 745

10.5.6 A Software-Pipelining Algorithm 749

10.5.7 Scheduling Acyclic Data-Dependence Graphs 749

10.5.8 Scheduling Cyclic Dependence Graphs 751

10.5.9 Improvements to the Pipelining Algorithms 758

10.5.10 Modular Variable Expansion 758

10.5.11 Conditional Statements 761

10.5.12 Hardware Support for Software Pipelining 762

10.5.13 Exercises for Section 10.5 763

10.6 Summary of CHAPTER10 765

10.7 References for CHAPTER10 766

11 Optimizing for Parallelism and Locality 769

11.1 Basic Concepts 771

11.1.1 Multiprocessors 772

11.1.2 Parallelism in Applications 773

11.1.3 Loop-Level Parallelism 775

11.1.4 Data Locality 777

11.1.5 Introduction to Affiine Transform Theory 778

11.2 Matrix Multiply An In-Depth Example 782

11.2.1 The Matrix-Multiplication Algorithm 782

11.2.2 Optimizations 785

11.2.3 Cache Interference 788

11.2.4 Exercises for Section 11.2 788

11.3 Iteration Spaces 788

11.3.1 Constructing Iteration Spaces from Loop Nests 788

11.3.2 Execution Order for Loop Nests 791

11.3.3 Matrix Formulation of Inequalities 791

11.3.4 Incorporating Symbolic Constants 793

11.3.5 Controlling the Order of Execution 793

11.3.6 Changing Axes 798

11.3.7 Exercises for Section 11.3 799

11.4 Affine Array Indexes 801

11.4.1 Affine Accesses 802

11.4.2 Affine and Nonaffine Accesses in Practice 803

11.4.3 Exercises for Section 11.4 804

11.5 Data Reuse 804

11.5.1 Types of Reuse 805

11.5.2 Self Reuse 806

11.5.3 Self-Spatial Reuse 809

11.5.4 Group Reuse 811

11.5.5 Exercises for Section 11.5 814

11.6 Array Data-Dependence Analysis 815

11.6.1 Definition of Data Dependence of Array Accesses 816

11.6.2 Integer Linear Programming 817

11.6.3 The GCDTest 818

11.6.4 Heuristics for Solving Integer Linear Programs 820

11.6.5 Solving General IntegerLinear Programs 823

11.6.6 Summary 825

11.6.7 Exercises for Section 11.6 826

11.7 Finding Synchronization-Free Parallelism 828

11.7.1 An Introductory Example 828

11.7.2 Affine Space Partitions 830

11.7.3 Space-Partition Constraints 831

11.7.4 Solving Space-Partition Constraints 835

11.7.5 A Simple Code-Generation Algorithm 838

11.7.6 Eliminating Empty Iterations 841

11.7.7 Eliminating Tests from Innermost Loops 844

11.7.8 Source-Code Transforms 846

11.7.9 Exercises for Section 11.7 851

11.8 Synchronization Between Parallel Loops 853

11.8.1 A Constant Number of Synchronizations 853

11.8.2 Program-Dependence Graphs 854

11.8.3 Hierarchical Time 857

11.8.4 The Parallelization Algorithm 859

11.8.5 Exercises for Section 11.8 860

11.9 Pipelining 861

11.9.1 What is Pipelining？ 861

11.9.2 Successive Over-Relaxation （SOR）An Example 863

11.9.3 Fully Permutable Loops 864

11.9.4 Pipelining Fully Permutable Loops 864

11.9.5 General Theory 867

11.9.6 Time-Partition Constraints 868

11.9.7 Solving Time-Partition Constraints by Farkas’ Lemma 872

11.9.8 Code Transformations 875

11.9.9 Parallelism With Minimum Synchronization 880

11.9.10 Exercises for Section 11.9 882

11.10 Locality Optimizations 884

11.10.1 Temporal Locality of Computed Data 885

11.10.2 Array Contraction 885

11.10.3 Partition Interleaving 887

11.10.4 Putting it All Together 890

11.10.5 Exercises for Section 11.10 892

11.11 Other Uses of Affine Transforms 893

11.11.1 Distributed memory machines 894

11.11.2 Multi-Instruction-Issue Processors 895

11.11.3 Vector and SIMD Instructions 895

11.11.4 Prefetching 896

11.12 Summary of CHAPTER11 897

11.13 References for CHAPTER11 899

12 Interprocedural Analysis 903

12.1 Basic Concepts 904

12.1.1 Call Graphs 904

12.1.2 Context Sensitivity 906

12.1.3 Call Strings 908

12.1.4 Cloning-Based Context-Sensitive Analysis 910

12.1.5 Summary-Based Context-Sensitive Analysis 911

12.1.6 Exercises for Section 12.1 914

12.2 Why Interprocedural Analysis？ 916

12.2.1 Virtual Method Invocation 916

12.2.2 Pointer Alias Analysis 917

12.2.3 Parallelization 917

12.2.4 Detection of Software Errors and Vulnerabilities 917

12.2.5 SQL Injection 918

12.2.6 Buffer Overflow 920

12.3 A Logical Representation of Data Flow 921

12.3.1 Introduction to Datalog 921

12.3.2 Datalog Rules 922

12.3.3 Intensional and Extensional Predicates 924

12.3.4 Execution of Datalog Programs 927

12.3.5 Incremental Evaluation of Datalog Programs 928

12.3.6 Problematic Datalog Rules 930

12.3.7 Exercises for Section 12.3 932

12.4 A Simple Pointer-Analysis Algorithm 933

12.4.1 Why is Pointer Analysis Difficult 934

12.4.2 A Model for Pointers and References 935

12.4.3 Flow Insensitivity 936

12.4.4 The Formulation in Datalog 937

12.4.5 Using Type Information 938

12.4.6 Exercises for Section 12.4 939

12.5 Context-Insensitive Interprocedural Analysis 941

12.5.1 Effects of a Method Invocation 941

12.5.2 Call Graph Discovery in Datalog 943

12.5.3 Dynamic Loading and Reflection 944

12.5.4 Exercises for Section 12.5 945

12.6 Context-Sensitive Pointer Analysis 945

12.6.1 Contexts and Call Strings 946

12.6.2 Adding Context to Datalog Rules 949

12.6.3 Additional Observations About Sensitivity 949

12.6.4 Exercises for Section 12.6 950

12.7 Datalog Implementation by BDD’s 951

12.7.1 Binary Decision Diagrams 951

12.7.2 Transformations on BDD’s 953

12.7.3 Representing Relations by BDD’s 954

12.7.4 Relational Operations as BDD Operations 954

12.7.5 Using BDD’s for Points-to Analysis 957

12.7.6 Exercises for Section 12.7 958

12.8 Summary of CHAPTER12 958

12.9 References for CHAPTER12 961

A A Complete Front End 965

A.1 The Source Language 965

A.2 Main 966

A.3 Lexical Analyzer 967

A.4 Symbol Tables and Types 970

A.5 Intermediate Code for Expressions 971

A.6 Jumping Code for Boolean Expressions 974

A.7 Intermediate CodeforStatements 978

A.8 Parser 981

A.9 Creating the Front End 986

B Finding Linearly Independent Solutions 989

Index 993