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GPU Scaling: From Personal Supercomputing to the Cloud

GPU Scaling: From Personal Supercomputing to the Cloud

Yaser Jararweh, Moath Jarrah, Abdelkader Bousselham
Copyright: © 2016 |Pages: 12
ISBN13: 9781466694668|ISBN10: 1466694661|EISBN13: 9781466694675
DOI: 10.4018/978-1-4666-9466-8.ch105
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MLA

Jararweh, Yaser, et al. "GPU Scaling: From Personal Supercomputing to the Cloud." Web-Based Services: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2016, pp. 2373-2384. https://doi.org/10.4018/978-1-4666-9466-8.ch105

APA

Jararweh, Y., Jarrah, M., & Bousselham, A. (2016). GPU Scaling: From Personal Supercomputing to the Cloud. In I. Management Association (Ed.), Web-Based Services: Concepts, Methodologies, Tools, and Applications (pp. 2373-2384). IGI Global. https://doi.org/10.4018/978-1-4666-9466-8.ch105

Chicago

Jararweh, Yaser, Moath Jarrah, and Abdelkader Bousselham. "GPU Scaling: From Personal Supercomputing to the Cloud." In Web-Based Services: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 2373-2384. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-4666-9466-8.ch105

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Abstract

Current state-of-the-art GPU-based systems offer unprecedented performance advantages through accelerating the most compute-intensive portions of applications by an order of magnitude. GPU computing presents a viable solution for the ever-increasing complexities in applications and the growing demands for immense computational resources. In this paper the authors investigate different platforms of GPU-based systems, starting from the Personal Supercomputing (PSC) to cloud-based GPU systems. The authors explore and evaluate the GPU-based platforms and the authors present a comparison discussion against the conventional high performance cluster-based computing systems. The authors' evaluation shows potential advantages of using GPU-based systems for high performance computing applications while meeting different scaling granularities.

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