On green and energy-aware GPU computing for scientific applications
Recently, modern graphics processing unit (GPU) has gained the reputation of computational accelerator that can achieve a significant increase in performance by reducing execution time for the different type of scientific application that demand high performance computing. While modern GPUs reduce t...
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Society of Digital Information and Wireless Communications (SDIWC)
2015
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my.upm.eprints.590352018-02-21T06:13:11Z http://psasir.upm.edu.my/id/eprint/59035/ On green and energy-aware GPU computing for scientific applications Abdur Rahman Abdul Hamid, Nor Asilah Wati Abdul Rahiman, Amir Rizaan Syed, Toqeer Ali Zafar, Basim Recently, modern graphics processing unit (GPU) has gained the reputation of computational accelerator that can achieve a significant increase in performance by reducing execution time for the different type of scientific application that demand high performance computing. While modern GPUs reduce the execution time of a parallel application as compared to the CPU implementation, but this performance is sometimes achieved at an expense of considerable power and energy consumption. This paper seeks to characterize and explore the impression of high power consumption in a GPU. We examine this notion by reviewing techniques used by researchers to analyze the performance, power, and energy characteristics of GPUs that are utilized for scientific computing. These studies consider applications that run on a traditional CPU setup, and the transformed parallel applications, running on hybrid CPU+GPU environment. These studies indicated that the heterogeneous CPU+GPU environment delivers an energy-aware and sustainable product that is much better than a traditional CPU application. Society of Digital Information and Wireless Communications (SDIWC) 2015 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/59035/1/38-3.pdf Abdur Rahman and Abdul Hamid, Nor Asilah Wati and Abdul Rahiman, Amir Rizaan and Syed, Toqeer Ali and Zafar, Basim (2015) On green and energy-aware GPU computing for scientific applications. In: Third International Conference on Green Computing, Technology and Innovation (ICGCTI2015), 8-10 Dec. 2015, Universiti Putra Malaysia. (pp. 31-37). |
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Recently, modern graphics processing unit (GPU) has gained the reputation of computational accelerator that can achieve a significant increase in performance by reducing execution time for the different type of scientific application that demand high performance computing. While modern GPUs reduce the execution time of a parallel application as compared to the CPU implementation, but this performance is sometimes achieved at an expense of considerable power and energy consumption. This paper seeks to characterize and explore the impression of high power consumption in a GPU. We examine this notion by reviewing techniques used by researchers to analyze the performance, power, and energy characteristics of GPUs that are utilized for scientific computing. These studies consider applications that run on a traditional CPU setup, and the transformed parallel applications, running on hybrid CPU+GPU environment. These studies indicated that the heterogeneous CPU+GPU environment delivers an energy-aware and sustainable product that is much better than a traditional CPU application. |
format |
Conference or Workshop Item |
author |
Abdur Rahman Abdul Hamid, Nor Asilah Wati Abdul Rahiman, Amir Rizaan Syed, Toqeer Ali Zafar, Basim |
spellingShingle |
Abdur Rahman Abdul Hamid, Nor Asilah Wati Abdul Rahiman, Amir Rizaan Syed, Toqeer Ali Zafar, Basim On green and energy-aware GPU computing for scientific applications |
author_facet |
Abdur Rahman Abdul Hamid, Nor Asilah Wati Abdul Rahiman, Amir Rizaan Syed, Toqeer Ali Zafar, Basim |
author_sort |
Abdur Rahman |
title |
On green and energy-aware GPU computing for scientific applications |
title_short |
On green and energy-aware GPU computing for scientific applications |
title_full |
On green and energy-aware GPU computing for scientific applications |
title_fullStr |
On green and energy-aware GPU computing for scientific applications |
title_full_unstemmed |
On green and energy-aware GPU computing for scientific applications |
title_sort |
on green and energy-aware gpu computing for scientific applications |
publisher |
Society of Digital Information and Wireless Communications (SDIWC) |
publishDate |
2015 |
url |
http://psasir.upm.edu.my/id/eprint/59035/1/38-3.pdf http://psasir.upm.edu.my/id/eprint/59035/ |
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