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Multicore and GPU Programming: An Integrated Approach, Second Edition offers broad coverage of key parallel computing skillsets, including multicore CPU programming and manycore "massively parallel" computing. Using threads, OpenMP, MPI, CUDA and other current tools, the book teaches the design and development of software capable of taking advantage of today’s computing platforms that incorporate CPU and GPU hardware. In addition, it explains how to transition from sequential programming to a parallel computing paradigm. Presenting material refined over more than a decade of teaching parallel computing, author Gerassimos Barlas minimizes the challenge with multiple examples, extensive case studies, and full source code.
By using this book, readers will better understand how to develop programs that run over distributed memory machines using MPI, create multi-threaded applications with either libraries or directives, write optimized applications that balance the workload between available computing resources, and profile and debug programs targeting multicore machines.
- Includes comprehensive coverage of all major multicore programming tools, including threads, OpenMP, MPI, and CUDA, with coverage of OpenCL and OpenACC added
- Demonstrates parallel programming design patterns and examples of how different tools and paradigms can be integrated for superior performance
- Updates in the second edition include the use of the C++14 standard for all sample code, a new chapter on concurrent data structures, and the latest research on load balancing
- Includes downloadable source code, examples and instructor support materials on the book’s companion website
Graduate students in parallel computing courses covering both traditional and GPU computing (or a two-semester sequence); professionals and researchers looking to master parallel computing
Part A: Introduction
2. Multicore and Parallel Program Design
Part B: Programming with Threads and Processes
3. Shared-memory Programming: Threads
4. Concurrent Data Structures
5. Distributed Memory Programming MPI
6. GPU Programming: CUDA
7. GPU Programming: OpenCL
Part C: Higher-level Programming
8. Shared-memory Programming: OpenMP
9. GPU Programming: OpenACC
10. The Thrust Template Library
Part D: Advanced Topics
11. Load Balancing
- No. of pages:
- © Morgan Kaufmann 2021
- 1st December 2021
- Morgan Kaufmann
- Paperback ISBN:
Gerassimos Barlas is a Professor with the Computer Science & Engineering Department, American University of Sharjah, Sharjah, UAE. His research interest includes parallel algorithms, development, analysis and modeling frameworks for load balancing, and distributed Video on-Demand. Prof. Barlas has taught parallel computing for more than 12 years, has been involved with parallel computing since the early 90s, and is active in the emerging field of Divisible Load Theory for parallel and distributed systems.
Professor, Computer Science and Engineering Department, American University of Sharjah, UAE
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