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Towards a methodology for creating time-critical, cloud-based CUDA applications

Knight, Louise ORCID: https://orcid.org/0000-0003-1431-197X, Stefanic, Polona, Cigale, Matej, Jones, Andrew C. and Taylor, Ian J. ORCID: https://orcid.org/0000-0001-5040-0772 2018. Towards a methodology for creating time-critical, cloud-based CUDA applications. Presented at: IT4RIs 18: Interoperable infrastructures for interdisciplinary big data sciences- Time critical applications and infrastructure optimization, Amsterdam, The Netherlands, 18 January 2018. Proceedings of the 3rd edition in the series of workshop on Interoperable infrastructures for interdisciplinary big data sciences (IT4RIs 18). 10.5281/zenodo.1162877

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Abstract

CUDA has been used in many different application domains, not all of which are specifically image processing related. There is the opportunity to use multiple and/or distributed CUDA resources in cloud facilities such as Amazon Web Services (AWS), in order to obtain enhanced processing power and to satisfy time-critical requirements which cannot be satisfied using a single CUDA resource. In particular, this would provide enhanced ability for processing Big Data, especially in conjunction with distributed file systems (for example). In this paper, we present a survey of time-critical CUDA applications, identifying requirements and concepts that they tend to have in common. In particular, we investigate the terminology used for Quality of Service metrics, and present a taxonomy which summarises the underlying concepts and maps these terms to the diverse terminology used. We also survey typical requirements for developing, deploying and managing such applications. Given these requirements, we consider how the SWITCH platform can in principle support the entire life-cycle of time-critical CUDA application development and cloud deployment, and identify specific extensions which would be needed in order fully to support this particular class of time-critical cloud applications.

Item Type: Conference or Workshop Item (Paper)
Date Type: Submission
Status: Unpublished
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Funders: European Commission
Related URLs:
Date of First Compliant Deposit: 14 February 2018
Last Modified: 14 Dec 2022 03:09
URI: https://orca.cardiff.ac.uk/id/eprint/109016

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