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- Title: CUDA Tutorial
- Author(s) Putt Sakdhnagool
- Publisher: ReadTheDocs
- Paperback: N/A
- eBook: HTML and PDF
- Language: English
- ISBN-10/ASIN: N/A
- ISBN-13: N/A
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This book introduces the essentials of CUDA C programming clearly and concisely, quickly guiding you from running sample programs to building your own code, assumes no specialized background in GPU-based or parallel computing.
About the Authors- N/A
- Computer Graphics, 3D, Animation and Imaging
- Parallel, Concurrent Computing and Programming
- C Programming
- Computer and Video Game Programming
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- CUDA Tutorial (Putt Sakdhnagool)
- The Mirror Site (1) - PDF
- The Mirror Site (2) - PDF
- The Mirror Site (3) - PDF
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Parallel Programming with CUDA: Architecture, Analysis, Application
This book offers a detailed guide to CUDA with a grounding in parallel fundamentals. With CUDA, you can use a desktop PC for work that would have previously required a large cluster of PCs or access to a High-Performance Computing (HPC) facility.
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CUDA Succinctly (Chris Rose)
This book discusses CUDA hardware and software in greater detail and covering both CUDA and Kepler. Every CUDA developer, from the casual to the most sophisticated, will find something here of interest and immediate usefulness.
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GPU Gems 3 by Addison-Wesley (Hubert Nguyen)
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GPU Gems 2: Programming for High-Performance Graphics
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GPU Gems: Techniques, Tips and Tricks for Real-Time Graphics
It focuses on the programmable graphics pipeline available in today's graphics processing units (GPUs) and highlights quick and dirty tricks used by leading developers, as well as fundamental, performance-conscious techniques.
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The Cg Tutorial: The Guide to Programmable Real-Time Graphics
Cg (C for graphics) is a complete programming environment for the fast creation of special effects and real-time cinematic quality experiences. This book explains how to implement both basic and advanced techniques for today's programmable GPU architectures.
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BIG CPU, BIG DATA: Solving the World's Toughest Problems
This book teaches you how to write parallel programs for multicore machines, compute clusters, GPU accelerators, and big data map-reduce jobs, in the Java language, with the free, easy-to-use, object-oriented Parallel Java 2 Library.
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Programming on Parallel Machines: GPU, Multicore, Clusters, etc.
The main goal of the book is to present parallel programming techniques that can be used in many situations for many application areas and which enable the reader to develop correct and efficient parallel programs.
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