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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: © 2014 |Volume: 9 |Issue: 4 |Pages: 11
ISSN: 1554-1045|EISSN: 1554-1053|EISBN13: 9781466655324|DOI: 10.4018/ijitwe.2014100102
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MLA

Jararweh, Yaser, et al. "GPU Scaling: From Personal Supercomputing to the Cloud." IJITWE vol.9, no.4 2014: pp.13-23. http://doi.org/10.4018/ijitwe.2014100102

APA

Jararweh, Y., Jarrah, M., & Bousselham, A. (2014). GPU Scaling: From Personal Supercomputing to the Cloud. International Journal of Information Technology and Web Engineering (IJITWE), 9(4), 13-23. http://doi.org/10.4018/ijitwe.2014100102

Chicago

Jararweh, Yaser, Moath Jarrah, and Abdelkader Bousselham. "GPU Scaling: From Personal Supercomputing to the Cloud," International Journal of Information Technology and Web Engineering (IJITWE) 9, no.4: 13-23. http://doi.org/10.4018/ijitwe.2014100102

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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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