编译原理技术与工具_在线百科全书查询
编译原理技术与工具
图书信息
出版社: 人民邮电出版社; 第1版 (2008年2月1日)
丛书名: 国外著名高等院校信息科学与技术优秀教材
平装: 1009页
正文语种: 简体中文, 英语
开本: 16
ISBN: 9787115172655
条形码: 9787115172655
尺寸: 23.8 x 17 x 4 cm
重量: 1.3 Kg
作者简介
作者：(美国)Alfred V.Aho (美国)Monica S.Lam
Alfred V.Aho是哥伦比亚大学的Lawrence Gussman计算机科学教授。Aho教授多次获奖，其中包括哥伦比亚校友会颁发的2003年度Great Teacher奖和电子与电器工程师协会的John von Neumann奖章。他是美国国家工程院院士，以AACM和IEEE的会员。
内容简介
《编译原理技术与工具(第2版)》共12章。第一章是一些关于学习动机的资料，同时也给出了一些关于计算机体系结构和程序设计语言原理的背景知识。第二章开发了一个缩微的编译器，并介绍了很多重要的概念，这些概念将在后面的各个章节中深入介绍。这个编译器本身在附录中给出。第三章讨论了词法分析、正则表达式、有穷状态自动机和词法分析器的生成工具，这些内容是各种正文处理的基础。第四章讨论了主流的语法分析方法，包括自顶向下方法（递归下降法， LL技术）和自底向上方法（LR技术和它的变体）。第五章介绍了语法制导定义和语法制导翻译的基本思想。第六章介绍了如何使用第五章中的理论为一个典型的程序设计语言生成中间代码。第七章讨论了运行时刻环境，主要是运行时刻栈的管理和垃圾收集机制。第八章介绍了关于目标代码生成的内容，主要讨论了基本块的构造，从表达式和基本块生成代码的方法，以及寄存器分配技术。第九章介绍了代码优化技术，包括流图、数据流分析框架以及求解这些框架的迭代算法。第十章讨论了指令级优化。该章的重点是从小段指令代码中抽取并行性，并在那些可以同时做多件事情的单处理器上调度这些指令。第十一章讲的是大规模并行的检测和利用。这章的重点是数值计算代码，这些代码具有对多维数组进行遍历的紧致循环。第十二章介绍的是关于过程间分析技术的内容，讨论了指针分析、别名和数据流分析，这些分析中都考虑了到达代码中某个给定点时的过程调用序列。
目录
1 Introduction 1
1.1 Language Processors 1
1.1.1 Exercises for Section1.1 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 Phasesin to Passes 11
1.2.9 Compiler-Construction Tools 12
1.3 The Evolution of Programming Languages 12
1.3.1 The Moveto Higher-level Languages 13
1.3.2 Impactson Compilers 14
1.3.3 Exercises for Section1.3 14
1.4 The Science of Building a Compiler 15
1.4.1 Modelingin 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 Environmentsand States 26
1.6.3 Static Scopeand 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 Section1.6 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 Section2.3 60
2.4 Parsing 60
2.4.1 Top-Down Parsing 61
2.4.2 Predictive Parsing 64
2.4.3 When to Use -Productions 65
2.4.4 Designinga 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 and Concrete Syntax 69
2.5.2 Adaptingthe Translation Scheme 70
2.5.3 Procedures for the Nonterminals 72
2.5.4 Simplifying the Translator 732.5.5 The Complete Program 74
2.6 Lexical Analysis 76
2.6.1 Removalof White Spaceand Comments 77
2.6.2 Reading A head 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 Symbol Tables 89
2.8 Intermediate Code Generation 91
2.8.1 Two Kinds of Intermediate Representations 91
2.8.2 Constructionof 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 Chapter 2 105
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 Stringsand Languages 117
3.3.2 Operationson Languages 119
3.3.3 Regular Expressions 120
3.3.4 Regular Definitions 123
3.3.5 Extensionsof Regular Expressions 124
3.3.6 Exercises for Section 3.3 125
3.4 Recognitionof 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 Analyzer 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 Confiict Resolutionin 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 Stringsby 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 Conversionof 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 Chapter 3 187
3.11 References for Chapter 3 189
4 Syntax Analysis 191
4.1 Introduction 192
4.1.1 The Roleof 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-Free 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 LeftRecursion 212
4.3.4 Left Factoring 214
4.3.5 Non-Context-FreeLanguage 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 Precedenceand Associativity to Resolve Confiicts 279
4.8.2 The “Dangling-Else” Ambiguity 281
4.8.3 Error Recoveryin 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 Chapter 4 297
4.11 References for Chapter 4 300
5 Syntax-Directed Translation 303
5.1 Syntax-Directed Definitions 304
5.1.1 Inheritedand 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 ExercisesforSection5.5 352
5.6 Summary of Chapter 5 353
5.7 References for Chapter 5 354
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 Addressesand 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 Fieldsin 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 References 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 Functionsand 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 Switch-Statements 420
6.8.3 Exercises for Section 6.8 421
6.9 Intermediate Code for Procedures 422
6.10 Summary of Chapter 6 424
6.11 References for Chapter 6 425
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 Dataonthe Stack 438
7.2.5 Exercises for Section 7.2 440
7.3 Access to Nonlocal Dataon 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 AccessLinks 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 Localityin 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 for Section 7.5 470
7.6 Introduction to Trace-Based Collection 470
7.6.1 A Basic 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 Paralleland 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 Chapter 7 500
7.10 References for Chapter 7 502
8 Code Generation 505
8.1 Issuesin 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 Programand 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 Blocksand 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 Loadsand 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 Allocationand 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 Tilingan Input Tree 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 FromLabeled Expression Trees 568
8.10.3 Evaluating Expressions with an Insuficient Supply of Registers 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 Chapter 8 578
8.13 References for Chapter 8 579
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 Trans for mations 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 Variablesand Reductionin 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 Schemason 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 Framework 633
9.4.2 The Meet for the Constant-Propagation Framework 633
9.4.3 Transfer Functions for the Constant-Propagation Framework 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 TheLazy-Code-Motion Algorithm 646
9.5.6 Exercises for Section 9.5 655
9.6 Loopsin Flow Graphs 655
9.6.1 Dominators 656
9.6.2 Depth-First Ordering 660
9.6.3 Edgesina Depth-First Spanning Tree 661
9.6.4 Back Edgesand 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 Nonreducible Flow 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 Section 9.8 699
9.9 Summary of Chapter 9 700
9.10 References for Chapter 9 703
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 Finding Dependences Among Memory Accesses 712
10.2.3 Tradeoff Between Register Usage and Parallelism 713
10.2.4 Phase Ordering Between Register Allocation and Code Scheduling 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 Chapter 10 765
10.7 References for Chapter 10 766
11 Optimizing for Parallelism and Locality 769
11.1 Basic Concepts 771
11.1.1 Multiprocessors 772
11.1.2 Parallelismin Applications 773
11.1.3 Loop-Level Parallelism 775
11.1.4 Data Locality 777
11.1.5 Introduction to Affine Trans form Theory 778
11.2 Matrix Multiply:AnIn-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 Controllingthe Order of Execution 793
11.3.6 Changing Axes 798
11.3.7 Exercises for Section 11.3 799
11.4 AffineArray Indexes 801
11.4.1 Affine Accesses 802
11.4.2 Affineand 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 GCD Test 818
11.6.4 Heuristics for Solving Integer Linear Programs 820
11.6.5 Solving General Integer Linear 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 Asimple 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 Whatis 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 Trans for mations 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 Puttingit 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 Chapter 11 897
11.13 References for Chapter 11 899
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 Errorsand 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 DatalogRules 930
12.3.7 Exercises for Section 12.3 932
12.4 A SimplePointer-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 Formulationin 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 Discoveryin 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 CallStrings 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 Operationsas BDD Operations 954
12.7.5 Using BDD''s for Points-toAnalysis 957
12.7.6 Exercises for Section 12.7 958
12.8 Summary of Chapter 12 958
12.9 References for Chapter 12 961
A A Complete FrontEnd 965
A.1 The Source Language 965
A.2 Main 966
A.3 Lexical Analyzer 967
A.4 Symbol Tablesand Types 970
A.5 Intermediate Code for Expressions 971
A.6 Jumping Code for Boolean Expressions 974
A.7 Intermediate Code for Statements 978
A.8 Parser 981
A.9 Creatingthe FrontEnd 986
B Finding Linearly Independent Solutions 989
Index 993
