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Scientific Parallel Computing
L. Ridgway Scott, Terry Clark, & Babak Bagheri

Book Description | Reviews
Chapter 1 [in PDF format]

TABLE OF CONTENTS:

Preface ix
Notation xiii

Chapter 1. Introduction 1
1.1 Overview 1
1.2 What is parallel computing? 3
1.3 Performance 4
1.4 Why parallel? 11
1.5 Two simple examples 15
1.6 Mesh-based applications 24
1.7 Parallel perspectives 30
1.8 Exercises 33

Chapter 2. Parallel Performance 37

2.1 Summation example 37
2.2 Performance measures 38
2.3 Limits to performance 44
2.4 Scalability 48
2.5 Parallel performance analysis 56
2.6 Parallel payoff 59
2.7 Real world parallelism 64
2.8 Starting SPMD programming 66
2.9 Exercises 66

Chapter 3. Computer Architecture 71
3.1 PMS notation 71
3.2 Shared memory multiprocessor 75
3.3 Distributed memory multicomputer 79
3.4 Pipeline and vector processors 87
3.5 Comparison of parallel architectures 89
3.6 Taxonomies 92
3.7 Current trends 94
3.8 Exercises 95

Chapter 4. Dependences 99
4.1 Data dependences 100
4.2 Loop-carried data dependences 103
4.3 Dependence examples 110
4.4 Testing for loop-carried dependences 112
4.5 Loop transformations 114
4.6 Dependence examples continued 120
4.7 Exercises 123

Chapter 5. Parallel Languages 127
5.1 Critical factors 129
5.2 Command and control 134
5.3 Memory models 136
5.4 Shared memory programming 139
5.5 Message passing 143
5.6 Examples and comments 148
5.7 Parallel language developments 153
5.8 Exercises 154

Chapter 6. Collective Operations 157
6.1 The @notation 157
6.2 Tree/ring algorithms 158
6.3 Reduction operations 162
6.4 Reduction operation applications 164
6.5 Parallel prefix algorithms 168
6.6 Performance of reduction operations 169
6.7 Data movement operations 173
6.8 Exercises 174

Chapter 7. Current Programming Standards 177
7.1 Introduction to MPI 177
7.2 Collective operations in MPI 181
7.3 Introduction to POSIX threads 184
7.4 Exercises 187

Chapter 8. The Planguage Model 191
8.1 I P language details 192
8.2 Ranges and arrays 198
8.3 Reduction operations in Pfortran 200
8.4 Introduction to PC 204
8.5 Reduction operations in PC 206
8.6 Planguages versus message passing 207
8.7 Exercises 208

Chapter 9. High Performance Fortran 213
9.1 HPF data distribution directives 214
9.2 Other mechanisms for expressing concurrency 219
9.3 Compiling HPF 220
9.4 HPF comparisons and review 221
9.5 Exercises 222

Chapter 10. Loop Tiling 227
10.1 Loop tiling 227
10.2 Work vs.data decomposition 228
10.3 Tiling in OpenMP 228
10.4 Teams 232
10.5 Parallel regions 233
10.6 Exercises 234

Chapter 11. Matrix Eigen Analysis 237
11.1 The Leslie matrix model 237
11.2 The power method 242
11.3 A parallel Leslie matrix program 244
11.4 Matrix-vector product 249
11.5 Power method applications 251
11.6 Exercises 253

Chapter 12. Linea Systems 257
12.1 Gaussian elimination 257
12.2 Solving triangular systems in parallel 262
12.3 Divide-and-conquer algorithms 271
12.4 Exercises 277
12.5 Projects 281

Chapter 13. Particle Dynamics 283
13.1 Model assumptions 284
13.2 Using Newton's third law 285
13.3 Further code complications 288
13.4 Pair list generation 290
13.5 Force calculation with a pair list 296
13.6 Performance of replication algorithm 299
13.7 Case study:particle dynamics in HPF 302
13.8 Exercises 307
13.9 Projects 310

Chapter 14. Mesh Methods 315
14.1 Boundary value problems 315
14.2 Iterative methods 319
14.3 Multigrid methods 322
14.4 Multidimensional problems 327
14.5 Initial value problems 328
14.6 Exercises 333
14.7 Projects 334

Chapter 15. Sorting 335
15.1 Introduction 335
15.2 Parallel sorting 337
15.3 Spatial sorting 342
15.4 Exercises 353
15.5 Projects 355

Bibliography 357
Index 369

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File created: 4/17/2014

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