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Integrating acceleration devices using CometCloud

Beach, Thomas, Rana, Omer Farooq and Avis, Nicholas John 2013. Integrating acceleration devices using CometCloud. Presented at: 1st ACM workshop on Optimization techniques for resources management in clouds, New York, NY, USA, 17-21 June 2013. Published in: Baraglia, R., Coppola, M. and Dazzi, P. eds. ORMaCloud '13: Proceedings of the first ACM workshop on Optimization techniques for resources management in clouds. New York, NY: ACM, pp. 17-24. 10.1145/2465823.2465824

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Abstract

Application accelerators can include GPUs, cell processors, FPGAs and other custom application specific integrated circuit (ASICs) based devices. A number of challenges arise when these devices must be integrated as part of a single computing environment, relating to both the diversity of devices and the supported programming models. One key challenge we consider here is the selection of the most appropriate device for accelerating a particular application. Our approach makes use of a broker-based matchmaking system, which attempts to compare the capability of a device with one or more application kernels, utilising the CometCloud tuple space-based coordination mechanism to facilitate the matchmaking process. We describe the architecture of our system and how it utilises performance prediction to select devices for particular application kernels. We demonstrate that within a highly dynamic HPC system, our approach can increase the performance of applications by using code porting techniques to the most suitable device found, also; (a) allowing the dynamic addition of new devices to the system, and (b) allowing applications to fall back and utilise the best alternative device available if the preferred device cannot be found or is unavailable.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Engineering
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: ACM
ISBN: 9781450319829
Last Modified: 04 Jun 2017 05:11
URI: http://orca.cf.ac.uk/id/eprint/49262

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