1st Edition

GPU Parallel Program Development Using CUDA

By Tolga Soyata Copyright 2018
476 Pages
by Chapman & Hall

476 Pages 54 B/W Illustrations
by Chapman & Hall

476 Pages 54 B/W Illustrations
by Chapman & Hall

GPU Parallel Program Development using CUDA teaches GPU programming by showing the differences among different families of GPUs. This approach prepares the reader for the next generation and future generations of GPUs. The book emphasizes concepts that will remain relevant for a long time, rather than concepts that are platform-specific. At the same time, the book also provides... Read more

Introduction to Parallelism and GPU Programming. Introduction to Pthreads. Introduction to Multi-threading. Multi-threading Analysis. Introduction to AWS and the first GPU program. Analysis of the first CUDA program. How to run programs outside Amazon, on a different Unix system. How to run programs outside Amazon, on a different Windows system. Introduction to GPU Multi-threading and Global Memory. In-depth look at Global Memory and GPU Threads. Introduction to Shared Memory. In-depth look at Shared Memory. Performance Bottlenecks in GPU Architecture. Compute Capability and PTX. Host-Device Data Movement Mechanism. CUDA Streaming. CUDA Atomics. OpenGL-CUDA Interoperability. OpenGL and Real-Time GPU Processing. Example Applications - Edge Detection (CUBLAS). Example Applications - Sophisticated Image Processing (CUFFT). Example Applications- Elastography Based Tumor Detection (CUSOLVER). Example Applications - Real-Time Face Recognition (OpenCV, CUBLAS).

Biography

Tolga Soyata is an associate professor in the Electrical and Computer Engineering department of SUNY Albany.