research-article

Cost vs. performance of VaR on accelerator platforms

Authors:

Mukul Majmudar,

Ciprian Docan,

Manish Parashar,

Christopher MartyAuthors Info & Claims

WHPCF '09: Proceedings of the 2nd Workshop on High Performance Computational Finance

Article No.: 9, Pages 1 - 8

https://doi.org/10.1145/1645413.1645422

Published: 15 November 2009 Publication History

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Abstract

The computation of value at risk (VaR) can be parallelized to boost performance, but different parallel platforms entail different gains in performance, as well as different costs. This paper explores the cost and performance tradeoffs inherent in the computation of VaR when implemented on different parallel platforms.

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Cited By

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Varghese B(2018)The hardware accelerator debateComputers and Electrical Engineering10.1016/j.compeleceng.2015.01.01246:C(157-175)Online publication date: 27-Dec-2018
https://dl.acm.org/doi/10.1016/j.compeleceng.2015.01.012
Burke NRau-Chaplin AVarghese B(2016)Computing probable maximum loss in catastrophe reinsurance portfolios on multi-core and many-core architecturesConcurrency and Computation: Practice & Experience10.1002/cpe.369528:3(836-847)Online publication date: 10-Mar-2016
https://dl.acm.org/doi/10.1002/cpe.3695
Varghese BBarker A(2014)Are Clouds Ready to Accelerate Ad Hoc Financial Simulations?Proceedings of the 2014 IEEE/ACM International Symposium on Big Data Computing10.1109/BDC.2014.9(54-63)Online publication date: 8-Dec-2014
https://dl.acm.org/doi/10.1109/BDC.2014.9
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Cost vs. performance of VaR on accelerator platforms

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Information

Published In

WHPCF '09: Proceedings of the 2nd Workshop on High Performance Computational Finance

November 2009

54 pages

ISBN:9781605587165

DOI:10.1145/1645413

Conference Chairs:
David Daly
IBM Thomas J. Watson Research Center
,
Maria Eleftheriou
IBM Thomas J. Watson Research Center
,
José Moreira
IBM Thomas J. Watson Research Center
,
Kyung Ryu
IBM Thomas J. Watson Research Center

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 November 2009

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Research-article

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SC '09

Sponsor:

SIGARCH

SC '09: International Conference for High Performance Computing, Networking, Storage and Analysis

November 15, 2009

Oregon, Portland

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Overall Acceptance Rate 8 of 10 submissions, 80%

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Cited By

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Varghese B(2018)The hardware accelerator debateComputers and Electrical Engineering10.1016/j.compeleceng.2015.01.01246:C(157-175)Online publication date: 27-Dec-2018
https://dl.acm.org/doi/10.1016/j.compeleceng.2015.01.012
Burke NRau-Chaplin AVarghese B(2016)Computing probable maximum loss in catastrophe reinsurance portfolios on multi-core and many-core architecturesConcurrency and Computation: Practice & Experience10.1002/cpe.369528:3(836-847)Online publication date: 10-Mar-2016
https://dl.acm.org/doi/10.1002/cpe.3695
Varghese BBarker A(2014)Are Clouds Ready to Accelerate Ad Hoc Financial Simulations?Proceedings of the 2014 IEEE/ACM International Symposium on Big Data Computing10.1109/BDC.2014.9(54-63)Online publication date: 8-Dec-2014
https://dl.acm.org/doi/10.1109/BDC.2014.9
Mencer OVynckier ESpooner JGirdlestone SCharlesworth OSmelyanskiy MDixon MDaly DEleftheriou MMoreira JRyu K(2011)Finding the right level of abstraction for minimizing operational expenditureProceedings of the fourth workshop on High performance computational finance10.1145/2088256.2088262(13-18)Online publication date: 13-Nov-2011
https://dl.acm.org/doi/10.1145/2088256.2088262
Hong LZhong-hua LXue-bin C(2010)The Applications and Trends of High Performance Computing in FinanceProceedings of the 2010 Ninth International Symposium on Distributed Computing and Applications to Business, Engineering and Science10.1109/DCABES.2010.45(193-197)Online publication date: 10-Aug-2010
https://dl.acm.org/doi/10.1109/DCABES.2010.45

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