📚 Programming Massively Parallel Processors : A Hands-On Approach P GuC
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Item specifics
- Condition
- Book Title
- Programming Massively Parallel Processors : A Hands-On Approach P
- ISBN
- 9780128119860
- Publication Year
- 2016
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Subject Area
- Computers
- Publication Name
- Programming Massively Parallel Processors : a Hands-On Approach
- Publisher
- Elsevier Science & Technology
- Item Length
- 9.2 in
- Subject
- Systems Architecture / General, Systems Architecture / Distributed Systems & Computing, Programming / General, Programming / Parallel
- Item Width
- 7.5 in
- Number of Pages
- 576 Pages
About this product
Product Identifiers
Publisher
Elsevier Science & Technology
ISBN-10
0128119861
ISBN-13
9780128119860
eBay Product ID (ePID)
228608949
Product Key Features
Number of Pages
576 Pages
Language
English
Publication Name
Programming Massively Parallel Processors : a Hands-On Approach
Subject
Systems Architecture / General, Systems Architecture / Distributed Systems & Computing, Programming / General, Programming / Parallel
Publication Year
2016
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Length
9.2 in
Item Width
7.5 in
Additional Product Features
Edition Number
3
Intended Audience
College Audience
LCCN
2016-957270
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
004.35
Table Of Content
1. Introduction2. Data parallel computing3. Scalable parallel execution4. Memory and data locality5. Performance considerations6. Numerical considerations7. Parallel patterns: convolution: An introduction to stencil computation8. Parallel patterns: prefix sum: An introduction to work efficiency in parallel algorithms9. Parallel patterns--parallel histogram computation: An introduction to atomic operations and privatization10. Parallel patterns: sparse matrix computation: An introduction to data compression and regularization11. Parallel patterns: merge sort: An introduction to tiling with dynamic input data identification12. Parallel patterns: graph search13. CUDA dynamic parallelism14. Application case study--non-Cartesian magnetic resonance imaging: An introduction to statistical estimation methods15. Application case study--molecular visualization and analysis16. Application case study--machine learning17. Parallel programming and computational thinking18. Programming a heterogeneous computing cluster19. Parallel programming with OpenACC20. More on CUDA and graphics processing unit computing21. Conclusion and outlook
Synopsis
Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in-depth. For this new edition, the authors have updated their coverage of CUDA, including coverage of newer libraries, such as CuDNN, moved content that has become less important to appendices, added two new chapters on parallel patterns, and updated case studies to reflect current industry practices. Teaches computational thinking and problem-solving techniques that facilitate high-performance parallel computing Utilizes CUDA version 7.5, NVIDIA's software development tool created specifically for massively parallel environments Contains new and updated case studies Includes coverage of newer libraries, such as CuDNN for Deep Learning, Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in-depth. For this new edition, the authors have updated their coverage of CUDA, including coverage of newer libraries, such as CuDNN, moved content that has become less important to appendices, added two new chapters on parallel patterns, and updated case studies to reflect current industry practices.
LC Classification Number
QA76.642.K57 2016
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