December 2012
Intermediate to advanced
514 pages
13h 6m
English
3.1 Data Parallelism
3.2 CUDA Program Structure
3.3 A Vector Addition Kernel
3.4 Device Global Memory and Data Transfer
3.5 Kernel Functions and Threading
3.6 Summary
3.7 Exercises
Our main objective is to teach the key concepts involved in writing massively parallel programs in a heterogeneous computing system. This requires many code examples expressed in a reasonably simple language that supports massive parallelism and heterogeneous computing. We have chosen CUDA C for our code examples and exercises. CUDA C is an extension to the popular C programming language1 with new keywords and application programming interfaces for programmers to take advantage of heterogeneous ...
Read now
Unlock full access