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Title: Architecture-aware approximate computing [Conference Object]
Authors: Karaköy, M.
Kışlal, O.
Tang, X.
Kandemir, M. T.
Arunachalam, M.
Keywords: Approximate computing
Manycore system
Issue Date: 2019
Publisher: Association for Computing Machinery, Inc
Source: 14th Joint Conference of International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2019 and IFIP Performance Conference 2019, SIGMETRICS/Performance 2019, 24 June 2019 through 28 June 2019, , 149007
Abstract: Observing that many application programs from different domains can live with less-than-perfect accuracy, existing techniques try to trade off program output accuracy with performance-energy savings. While these works provide point solutions, they leave three critical questions regarding approximate computing unanswered: (i) what is the maximum potential of skipping (i.e., not performing) data accesses under a given inaccuracy bound?; (ii) can we identify the data accesses to drop randomly, or is being architecture aware critical?; and (iii) do two executions that skip the same number of data accesses always result in the same output quality (error)? This paper first provides answers to these questions using ten multithreaded workloads, and then presents a program slicing-based approach that identifies the set of data accesses to drop. Results indicate 8.8% performance improvement and 13.7% energy saving are possible when we set the error bound to 2%, and the corresponding improvements jump to 15% and 25%, respectively, when the error bound is raised to 4%. © 2019 Copyright held by the owner/author(s).
ISBN: 9781450366786
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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