Programming on Parallel Machines; GPU, Multicore, Clusters and More
A textbook on parallel programming. The main programming language used is C/C++, but some of the code is in R.
Tag(s): Parallel Computing
Publication date: 01 Jun 2015
ISBN-10: n/a
ISBN-13: n/a
Paperback: 349 pages
Views: 9,072
Type: N/A
Publisher: n/a
License: Creative Commons Attribution-No Derivative Works 3.0 United States License
Post time: 19 Jul 2016 03:00:00
Programming on Parallel Machines; GPU, Multicore, Clusters and More
Norman Matloff wrote:Why is this book different from all other parallel programming books? It is aimed more on the practical end of things, in that:
- There is very little theoretical content, such as O() analysis, maximum theoretical speedup, PRAMs, directed acyclic graphs (DAGs) and so on.
- Real code is featured throughout.
- We use the main parallel platforms—OpenMP, CUDA and MPI—rather than languages that at this stage are largely experimental or arcane.
- The running performance themes—communications latency, memory/network contention, load balancing and so on—are interleaved throughout the book, discussed in the context of specific platforms or applications.
- Considerable attention is paid to techniques for debugging.
About The Author(s)
Dr. Norm Matloff is a professor of computer science at the University of California at Davis, and was formerly a professor of statistics at that university. He is a former database software developer in Silicon Valley, and has been a statistical consultant for firms such as the Kaiser Permanente Health Plan. He was born and raised in the Los Angeles area, and has a PhD in pure mathematics from UCLA, specializing in probability/functional analysis and statistics.
Dr. Norm Matloff is a professor of computer science at the University of California at Davis, and was formerly a professor of statistics at that university. He is a former database software developer in Silicon Valley, and has been a statistical consultant for firms such as the Kaiser Permanente Health Plan. He was born and raised in the Los Angeles area, and has a PhD in pure mathematics from UCLA, specializing in probability/functional analysis and statistics.