Scientific parallel computing

Title:

Personal Author:

Scott, L. Ridgway

Publication Information:

Princeton, NJ : Princeton University Press, 2005

ISBN:

9780691119359

Subject Term:

Parallel processing (Electronic computers)

Added Author:

Clark, Terry, 1954-

Bagheri, Babak

Available:*

Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ JB	30000010103382	QA76.58 S36 2005	Open Access Book	Book	Searching... Unknown
Searching... PSZ KL	30000010102329	QA76.58 S36 2005	Open Access Book	Book	Searching... Unknown

What does Google's management of billions of Web pages have in common with analysis of a genome with billions of nucleotides? Both apply methods that coordinate many processors to accomplish a single task. From mining genomes to the World Wide Web, from modeling financial markets to global weather patterns, parallel computing enables computations that would otherwise be impractical if not impossible with sequential approaches alone. Its fundamental role as an enabler of simulations and data analysis continues an advance in a wide range of application areas.

Scientific Parallel Computing is the first textbook to integrate all the fundamentals of parallel computing in a single volume while also providing a basis for a deeper understanding of the subject. Designed for graduate and advanced undergraduate courses in the sciences and in engineering, computer science, and mathematics, it focuses on the three key areas of algorithms, architecture, languages, and their crucial synthesis in performance.

The book's computational examples, whose math prerequisites are not beyond the level of advanced calculus, derive from a breadth of topics in scientific and engineering simulation and data analysis. The programming exercises presented early in the book are designed to bring students up to speed quickly, while the book later develops projects challenging enough to guide students toward research questions in the field. The new paradigm of cluster computing is fully addressed. A supporting web site provides access to all the codes and software mentioned in the book, and offers topical information on popular parallel computing systems.

Integrates all the fundamentals of parallel computing essential for today's high-performance requirements
Ideal for graduate and advanced undergraduate students in the sciences and in engineering, computer science, and mathematics
Extensive programming and theoretical exercises enable students to write parallel codes quickly
More challenging projects later in the book introduce research questions
New paradigm of cluster computing fully addressed
Supporting web site provides access to all the codes and software mentioned in the book

Author Notes

L. Ridgway Scott is Louis Block Professor of Computer Science and of Mathematics at the University of Chicago. He is the coauthor of The Mathematical Theory of Finite Element Methods . Terry Clark is Assistant Professor of Computer Science in the Department of Electrical Engineering and Computer Science at the University of Kansas. Babak Bagheri is a software architect at PROS Revenue Management, a company that designs software for pricing and revenue management. Scott, Clark, and Bagheri codeveloped the P-languages.

Reviews 1

Choice Review

Scott (computer science and mathematics, Univ. of Chicago), Clark (computer science, Univ. of Kansas), and Bagheri have prepared a thorough treatment of the foundational and advanced principles of parallel computing. Their book is quite mathematical in its treatment of the topic, and as such, is most relevant to upper-division undergraduate and graduate-level courses of study. It covers topics ranging from computer architecture through parallel processing languages. It drills far into the details, to the particulars of how the underlying hardware elements (processors, switches, memory) participate in parallel algorithms and where those physical elements present limitations. The book comes with numerous examples, illustrations, and exercises. It also contains a rich bibliography to help with further research on this topic. If readers are seeking a book on grid computing, they will find an introduction to the topic here under the heading of mesh methods; for a more complete description they will need other resources. Nevertheless, this book provides an excellent background for understanding grids and parallel algorithms in general. ^BSumming Up: Recommended. Upper-division undergraduates through professionals. F. H. Wild III University of Rhode Island

Preface ix
Notation xiii
Chapter 1 Introduction	p. 1
1.1 Overview	p. 1
1.2 What is parallel computing?	p. 3
1.3 Performance	p. 4
1.4 Why parallel?	p. 11
1.5 Two simple examples	p. 15
1.6 Mesh-based applications	p. 24
1.7 Parallel perspectives	p. 30
1.8 Exercises	p. 33
Chapter 2 Parallel Performance	p. 37
2.1 Summation example	p. 37
2.2 Performance measures	p. 38
2.3 Limits to performance	p. 44
2.4 Scalability	p. 48
2.5 Parallel performance analysis	p. 56
2.6 Parallel payoff	p. 59
2.7 Real world parallelism	p. 64
2.8 Starting SPMD programming	p. 66
2.9 Exercises	p. 66
Chapter 3 Computer Architecture	p. 71
3.1 PMS notation	p. 71
3.2 Shared memory multiprocessor	p. 75
3.3 Distributed memory multicomputer	p. 79
3.4 Pipeline and vector processors	p. 87
3.5 Comparison of parallel architectures	p. 89
3.6 Taxonomies	p. 92
3.7 Current trends	p. 94
3.8 Exercises	p. 95
Chapter 4 Dependences	p. 99
4.1 Data dependences	p. 100
4.2 Loop-carried data dependences	p. 103
4.3 Dependence examples	p. 110
4.4 Testing for loop-carried dependences	p. 112
4.5 Loop transformations	p. 114
4.6 Dependence examples continued	p. 120
4.7 Exercises	p. 123
Chapter 5 Parallel Languages	p. 127
5.1 Critical factors	p. 129
5.2 Command and control	p. 134
5.3 Memory models	p. 136
5.4 Shared memory programming	p. 139
5.5 Message passing	p. 143
5.6 Examples and comments	p. 148
5.7 Parallel language developments	p. 153
5.8 Exercises	p. 154
Chapter 6 Collective Operations	p. 157
6.1 The @notation	p. 157
6.2 Tree/ring algorithms	p. 158
6.3 Reduction operations	p. 162
6.4 Reduction operation applications	p. 164
6.5 Parallel prefix algorithms	p. 168
6.6 Performance of reduction operations	p. 169
6.7 Data movement operations	p. 173
6.8 Exercises	p. 174
Chapter 7 Current Programming Standards	p. 177
7.1 Introduction to MPI	p. 177
7.2 Collective operations in MPI	p. 181
7.3 Introduction to POSIX threads	p. 184
7.4 Exercises	p. 187
Chapter 8 The Planguage Model	p. 191
8.1 I P language details	p. 192
8.2 Ranges and arrays	p. 198
8.3 Reduction operations in Pfortran	p. 200
8.4 Introduction to PC	p. 204
8.5 Reduction operations in PC	p. 206
8.6 Planguages versus message passing	p. 207
8.7 Exercises	p. 208
Chapter 9 High Performance Fortran	p. 213
9.1 HPF data distribution directives	p. 214
9.2 Other mechanisms for expressing concurrency	p. 219
9.3 Compiling HPF	p. 220
9.4 HPF comparisons and review	p. 221
9.5 Exercises	p. 222
Chapter 10 Loop Tiling	p. 227
10.1 Loop tiling	p. 227
10.2 Work vs.data decomposition	p. 228
10.3 Tiling in Open MP	p. 228
10.4 Teams	p. 232
10.5 Parallel regions	p. 233
10.6 Exercises	p. 234
Chapter 11 Matrix Eigen Analysis	p. 237
11.1 The Leslie matrix model	p. 237
11.2 The power method	p. 242
11.3 A parallel Leslie matrix program	p. 244
11.4 Matrix-vector product	p. 249
11.5 Power method applications	p. 251
11.6 Exercises	p. 253
Chapter 12 Linea Systems	p. 257
12.1 Gaussian elimination	p. 257
12.2 Solving triangular systems in parallel	p. 262
12.3 Divide-and-conquer algorithms	p. 271
12.4 Exercises	p. 277
12.5 Projects	p. 281
Chapter 13 Particle Dynamics	p. 283
13.1 Model assumptions	p. 284
13.2 Using Newton's third law	p. 285
13.3 Further code complications	p. 288
13.4 Pair list generation	p. 290
13.5 Force calculation with a pair list	p. 296
13.6 Performance of replication algorithm	p. 299
13.7 Case study:particle dynamics in HPF	p. 302
13.8 Exercises	p. 307
13.9 Projects	p. 310
Chapter 14 Mesh Methods	p. 315
14.1 Boundary value problems	p. 315
14.2 Iterative methods	p. 319
14.3 Multigrid methods	p. 322
14.4 Multidimensional problems	p. 327
14.5 Initial value problems	p. 328
14.6 Exercises	p. 333
14.7 Projects	p. 334
Chapter 15 Sorting	p. 335
15.1 Introduction	p. 335
15.2 Parallel sorting	p. 337
15.3 Spatial sorting	p. 342
15.4 Exercises	p. 353
15.5 Projects	p. 355
Bibliography	p. 357
Index	p. 369

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