×

Uh-oh, it looks like your Internet Explorer is out of date.

For a better shopping experience, please upgrade now.

CUDA Programming: A Developer's Guide to Parallel Computing with GPUs
     

CUDA Programming: A Developer's Guide to Parallel Computing with GPUs

by Shane Cook
 

See All Formats & Editions

ISBN-10: 0124159338

ISBN-13: 9780124159334

Pub. Date: 11/22/2012

Publisher: Elsevier Science

If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts

Overview

If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems.

  • Comprehensive introduction to parallel programming with CUDA, for readers new to both
  • Detailed instructions help readers optimize the CUDA software development kit
  • Practical techniques illustrate working with memory, threads, algorithms, resources, and more
  • Covers CUDA on multiple hardware platforms: Mac, Linux and Windows with several NVIDIA chipsets
  • Each chapter includes exercises to test reader knowledge

Product Details

ISBN-13:
9780124159334
Publisher:
Elsevier Science
Publication date:
11/22/2012
Series:
Applications of GPU Computing Series
Pages:
600
Sales rank:
1,337,069
Product dimensions:
7.68(w) x 9.08(h) x 1.02(d)

Table of Contents

  1. A Short History of Supercomputing
  2. Understanding Parallelism with GPUs
  3. CUDA Hardware Overview
  4. Setting Up Cuda
  5. Grids, Blocks, and Threads
  6. Memory Handling with CUDA
  7. Using CUDA in Practice
  8. Multi-CPU and Multi-GPU Solutions
  9. Optimizing Your Application
  10. Libraries and SDK
  11. Designing GPU-Based Systems
  12. Common Problems, Causes, and Solutions

Customer Reviews

Average Review:

Post to your social network

     

Most Helpful Customer Reviews

See all customer reviews