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GPU Computation and Platforms
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Author(s): K. Bhargavi (Siddaganga Institute of Technology, India)and Sathish Babu B. (Siddaganga Institute of Technology, India)
Copyright: 2016
Pages: 39
Source title:
Emerging Research Surrounding Power Consumption and Performance Issues in Utility Computing
Source Author(s)/Editor(s): Ganesh Chandra Deka (Regional Vocational Training Institute (RVTI) for Women, India), G.M. Siddesh (Ramaiah Institute of Technology, India), K. G. Srinivasa (M S Ramaiah Institute of Technology, Bangalore, India)and L.M. Patnaik (IISc, Bangalore, India)
DOI: 10.4018/978-1-4666-8853-7.ch007
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Abstract
The GPUs (Graphics Processing Unit) were mainly used to speed up computation intensive high performance computing applications. There are several tools and technologies available to perform general purpose computationally intensive application. This chapter primarily discusses about GPU parallelism, applications, probable challenges and also highlights some of the GPU computing platforms, which includes CUDA, OpenCL (Open Computing Language), OpenMPC (Open MP extended for CUDA), MPI (Message Passing Interface), OpenACC (Open Accelerator), DirectCompute, and C++ AMP (C++ Accelerated Massive Parallelism). Each of these platforms is discussed briefly along with their advantages and disadvantages.
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