Evaluation of High Density GPUs as Sustainable Smart City Infrastructure

Lei Shang; Ching Yeh Lin; Muhammad Atif; Allan Williams

doi:10.1109/UCC.2015.86

Evaluation of High Density GPUs as Sustainable Smart City Infrastructure

Lei Shang, Ching Yeh Lin, Muhammad Atif, Allan Williams

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

Internet of things (IoT) is driving the big data revolution in smart cities. In order to make informed, accurate and real-time decisions, smart cities have to invest in powerful computing infrastructure with the minimal total cost of ownership. Smart city infrastructure will need to process data from various scientific and engineering domains like weather variability, traffic management, disease control etc in real-time while keeping the operational costs to minimum. In this paper we build a case for using General Purpose GPUs (GPGPU) as an alternate to the traditional CPU based computing. Utilising the GPUs in development of smart city infrastructure is an attractive alternate as it provides an efficient computing capacity when compared with traditional CPU only solutions. However, we find that naive deployment of applications on high-density GPUs results in lower scalability and performance. We show that designing a NUMA and GPU affinity aware parallel execution model can lead to substantial speed-ups. Our results show that smart cities can save over 45% in infrastructure power and over 90% in data centre space if high-density GPU solutions are used.

Original language	English
Title of host publication	Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015
Editors	Omer Rana, Rajkumar Buyya, Ioan Raicu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	482-487
Number of pages	6
ISBN (Electronic)	9780769556970
DOIs	https://doi.org/10.1109/UCC.2015.86
Publication status	Published - 2015
Event	8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015 - Limassol, Cyprus Duration: 7 Dec 2015 → 10 Dec 2015

Publication series

Name	Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015

Conference

Conference	8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015
Country/Territory	Cyprus
City	Limassol
Period	7/12/15 → 10/12/15

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10.1109/UCC.2015.86

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Shang, L., Lin, C. Y., Atif, M., & Williams, A. (2015). Evaluation of High Density GPUs as Sustainable Smart City Infrastructure. In O. Rana, R. Buyya, & I. Raicu (Eds.), Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015 (pp. 482-487). Article 7431461 (Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/UCC.2015.86

Shang, Lei ; Lin, Ching Yeh ; Atif, Muhammad et al. / Evaluation of High Density GPUs as Sustainable Smart City Infrastructure. Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015. editor / Omer Rana ; Rajkumar Buyya ; Ioan Raicu. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 482-487 (Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015).

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title = "Evaluation of High Density GPUs as Sustainable Smart City Infrastructure",

abstract = "Internet of things (IoT) is driving the big data revolution in smart cities. In order to make informed, accurate and real-time decisions, smart cities have to invest in powerful computing infrastructure with the minimal total cost of ownership. Smart city infrastructure will need to process data from various scientific and engineering domains like weather variability, traffic management, disease control etc in real-time while keeping the operational costs to minimum. In this paper we build a case for using General Purpose GPUs (GPGPU) as an alternate to the traditional CPU based computing. Utilising the GPUs in development of smart city infrastructure is an attractive alternate as it provides an efficient computing capacity when compared with traditional CPU only solutions. However, we find that naive deployment of applications on high-density GPUs results in lower scalability and performance. We show that designing a NUMA and GPU affinity aware parallel execution model can lead to substantial speed-ups. Our results show that smart cities can save over 45% in infrastructure power and over 90% in data centre space if high-density GPU solutions are used.",

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author = "Lei Shang and Lin, {Ching Yeh} and Muhammad Atif and Allan Williams",

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year = "2015",

doi = "10.1109/UCC.2015.86",

language = "English",

series = "Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015",

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Shang, L, Lin, CY, Atif, M & Williams, A 2015, Evaluation of High Density GPUs as Sustainable Smart City Infrastructure. in O Rana, R Buyya & I Raicu (eds), Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015., 7431461, Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015, Institute of Electrical and Electronics Engineers Inc., pp. 482-487, 8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015, Limassol, Cyprus, 7/12/15. https://doi.org/10.1109/UCC.2015.86

Evaluation of High Density GPUs as Sustainable Smart City Infrastructure. / Shang, Lei; Lin, Ching Yeh; Atif, Muhammad et al.
Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015. ed. / Omer Rana; Rajkumar Buyya; Ioan Raicu. Institute of Electrical and Electronics Engineers Inc., 2015. p. 482-487 7431461 (Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Evaluation of High Density GPUs as Sustainable Smart City Infrastructure

AU - Shang, Lei

AU - Lin, Ching Yeh

AU - Atif, Muhammad

AU - Williams, Allan

PY - 2015

Y1 - 2015

N2 - Internet of things (IoT) is driving the big data revolution in smart cities. In order to make informed, accurate and real-time decisions, smart cities have to invest in powerful computing infrastructure with the minimal total cost of ownership. Smart city infrastructure will need to process data from various scientific and engineering domains like weather variability, traffic management, disease control etc in real-time while keeping the operational costs to minimum. In this paper we build a case for using General Purpose GPUs (GPGPU) as an alternate to the traditional CPU based computing. Utilising the GPUs in development of smart city infrastructure is an attractive alternate as it provides an efficient computing capacity when compared with traditional CPU only solutions. However, we find that naive deployment of applications on high-density GPUs results in lower scalability and performance. We show that designing a NUMA and GPU affinity aware parallel execution model can lead to substantial speed-ups. Our results show that smart cities can save over 45% in infrastructure power and over 90% in data centre space if high-density GPU solutions are used.

AB - Internet of things (IoT) is driving the big data revolution in smart cities. In order to make informed, accurate and real-time decisions, smart cities have to invest in powerful computing infrastructure with the minimal total cost of ownership. Smart city infrastructure will need to process data from various scientific and engineering domains like weather variability, traffic management, disease control etc in real-time while keeping the operational costs to minimum. In this paper we build a case for using General Purpose GPUs (GPGPU) as an alternate to the traditional CPU based computing. Utilising the GPUs in development of smart city infrastructure is an attractive alternate as it provides an efficient computing capacity when compared with traditional CPU only solutions. However, we find that naive deployment of applications on high-density GPUs results in lower scalability and performance. We show that designing a NUMA and GPU affinity aware parallel execution model can lead to substantial speed-ups. Our results show that smart cities can save over 45% in infrastructure power and over 90% in data centre space if high-density GPU solutions are used.

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KW - NUMA

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M3 - Conference contribution

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PB - Institute of Electrical and Electronics Engineers Inc.

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Shang L, Lin CY, Atif M, Williams A. Evaluation of High Density GPUs as Sustainable Smart City Infrastructure. In Rana O, Buyya R, Raicu I, editors, Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 482-487. 7431461. (Proceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015). doi: 10.1109/UCC.2015.86

Evaluation of High Density GPUs as Sustainable Smart City Infrastructure

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