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Advanced Topics GPU Programming and CUDA Architecture

Advanced Topics GPU Programming and CUDA Architecture

Mainak Adhikari, Sukhendu Kar
Copyright: © 2016 |Pages: 29
ISBN13: 9781466688537|ISBN10: 146668853X|EISBN13: 9781466688544
DOI: 10.4018/978-1-4666-8853-7.ch008
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MLA

Adhikari, Mainak, and Sukhendu Kar. "Advanced Topics GPU Programming and CUDA Architecture." Emerging Research Surrounding Power Consumption and Performance Issues in Utility Computing, edited by Ganesh Chandra Deka, et al., IGI Global, 2016, pp. 175-203. https://doi.org/10.4018/978-1-4666-8853-7.ch008

APA

Adhikari, M. & Kar, S. (2016). Advanced Topics GPU Programming and CUDA Architecture. In G. Deka, G. Siddesh, K. Srinivasa, & L. Patnaik (Eds.), Emerging Research Surrounding Power Consumption and Performance Issues in Utility Computing (pp. 175-203). IGI Global. https://doi.org/10.4018/978-1-4666-8853-7.ch008

Chicago

Adhikari, Mainak, and Sukhendu Kar. "Advanced Topics GPU Programming and CUDA Architecture." In Emerging Research Surrounding Power Consumption and Performance Issues in Utility Computing, edited by Ganesh Chandra Deka, et al., 175-203. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-4666-8853-7.ch008

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Abstract

Graphics processing unit (GPU), which typically handles computation only for computer graphics. Any GPU providing a functionally complete set of operations performed on arbitrary bits can compute any computable value. Additionally, the use of multiple graphics cards in one computer, or large numbers of graphics chips, further parallelizes the already parallel nature of graphics processing. CUDA (Compute Unified Device Architecture) is a parallel computing platform and programming model created by NVIDIA and implemented by the graphics processing units (GPUs). CUDA gives program developers direct access to the virtual instruction set and memory of the parallel computational elements in CUDA GPUs. This chapter first discuss some features and challenges of GPU programming and the effort to address some of the challenges with building and running GPU programming in high performance computing (HPC) environment. Finally this chapter point out the importance and standards of CUDA architecture.

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