Programming Massively Parallel Processors, Second Edition: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs.
This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing.
This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers.
- New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more
- Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism
- Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing
- Used Book in Good Condition
By: David B. Kirk, Published 2012-12-28 by Morgan Kaufmann
- CUDA by Example: An Introduction to General-Purpose GPU Programming
- Professional CUDA C Programming
- CUDA for Engineers: An Introduction to High-Performance Parallel Computing
- Computer Architecture, Fifth Edition: A Quantitative Approach (The Morgan Kaufmann Series in Computer Architecture and Design)
- CUDA Handbook: A Comprehensive Guide to GPU Programming, The
- CUDA Programming: A Developer's Guide to Parallel Computing with GPUs (Applications of Gpu Computing)
- Introduction to Algorithms, 3rd Edition (MIT Press)
- Deep Learning (Adaptive Computation and Machine Learning series)
- Deep Belief Nets in C++ and CUDA C: Volume 1: Restricted Boltzmann Machines and Supervised Feedforward Networks
- The C++ Programming Language, 4th Edition
Certain content that appears here comes from Amazon Services LLC. This content is provided 'as is' and is subject to change or removal at any time. Pricing and availability accurate as of 2017-02-23 11:30pm CST; please follow the links for current pricing.*