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Speculative program parallelization with scalable and decentralized runtime verification
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
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2014 (English)In: Runtime Verification, Springer Berlin/Heidelberg, 2014, 124-139 p.Conference paper, Published paper (Refereed)
Abstract [en]

Thread Level Speculation (TLS) is a dynamic code parallelization technique proposed to keep the software in pace with the advances in hardware,in particular, to automatically parallelize programs to take advantage of the multi-core processors. Being speculative, frameworks of this type unavoidably rely on verification systems that are similar to software transactional memory, and that require voluminous inter-thread communications or centralized registering of the performed memory accesses. The high degree of communication is against the basic principles of high performance parallel computing, does not scale with an increasing number of processor cores, and yields weak performance. Moreover, TLS systems often apply one unique parallelization strategy consisting in slicing a loop into several parallel speculative threads. Such a strategy is also against the basic principles since loops in the original serial code are not necessarily parallel and also, it is well-known that the parallel schedule must promote data locality which is crucial in obtaining good performance. This situation appeals to scalable and decentralized verification systems and new strategies to dynamically generate efficient parallel code resulting from advanced optimizing parallelizing transformations. Such transformations require a more complex verification system that allows intra-thread iterations to be reordered. In this paper, we propose a verification system of this kind, based on a model built at runtime and predicting a linear memory behavior. This strategy is part of the Apollo speculative code parallelizer which is based on an adaptation for dynamic usage of the polyhedral model.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2014. 124-139 p.
Series
Lecture Notes in Computer Science, 8734
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-235801DOI: 10.1007/978-3-319-11164-3_11ISI: 000358524900011ISBN: 978-3-319-11163-6 (print)OAI: oai:DiVA.org:uu-235801DiVA: diva2:762161
Conference
RV 2014, September 22–25, Toronto, Canada
Projects
UPMARC
Available from: 2014-10-01 Created: 2014-11-10 Last updated: 2018-01-11Bibliographically approved

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Jimborean, Alexandra

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  • apa
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