Cuda Programming: A Developer's Guide to Parallel Computing with Gpus

Abstract

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 Table of Contents A Short History of Supercomputing Understanding Parallelism with GPUs CUDA Hardware Overview Setting Up Cuda Grids, Blocks, and Threads Memory Handling with CUDA Using CUDA in Practice Multi-CPU and Multi-GPU Solutions Optimizing Your Application Libraries and SDK Designing GPU-Based Systems Common Problems, Causes, and Solutions

The authors' abstract, as published at the source., 2012 · DOI ↗