Programming Massively Parallel Processors: A Hands-on Approach

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

• Professional CUDA C Programming
• CUDA by Example: An Introduction to General-Purpose GPU Programming
• CUDA for Engineers: An Introduction to High-Performance Parallel Computing
• Deep Learning (Adaptive Computation and Machine Learning)
• Computer Architecture: A Quantitative Approach (The Morgan Kaufmann Series in Computer Architecture and Design)
• Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
• An Introduction to Parallel Programming
• GPU Parallel Program Development Using CUDA (Chapman & Hall/CRC Computational Science)
• Deep Learning with Python
• Effective Modern C++: 42 Specific Ways to Improve Your Use of C++11 and C++14