Tolga Soyata

Gpu Parallel Program Development Using Cuda

• Broschiertes Buch

Produktbeschreibung

This book teaches GPU programming by introducing CPU multi-threaded programming and bases GPU massively-parallel programming on this foundation. The differences among families of GPUs are also studied. The book also explores CUDA libraries, OpenCL, GPU programming with other languages and API libraries, and the deep learning library cuDNN

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Produktdetails

• Verlag: CRC Press
• Seitenzahl: 440
• Erscheinungstermin: 30. Juni 2020
• Englisch
• Abmessung: 254mm x 175mm x 23mm
• Gewicht: 816g
• ISBN-13: 9780367572242
• ISBN-10: 0367572249
• Artikelnr.: 73391166

Autorenporträt

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

Inhaltsangabe

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).