Enhancing computation-to-core assignment with physical location information

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dc.contributor.authorKislal, Orhanko
dc.contributor.authorKotra, Jagadishko
dc.contributor.authorTang, Xulongko
dc.contributor.authorKandemir, Mahmut Taylanko
dc.contributor.authorJung, Myoungsooko
dc.date.accessioned2019-12-13T12:29:23Z-
dc.date.available2019-12-13T12:29:23Z-
dc.date.created2019-11-28-
dc.date.created2019-11-28-
dc.date.issued2018-06-18-
dc.identifier.citation39th ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2018, pp.312 - 327-
dc.identifier.issn0362-1340-
dc.identifier.urihttp://hdl.handle.net/10203/269575-
dc.description.abstractGoing beyond a certain number of cores in modern architectures requires an on-chip network more scalable than conventional buses. However, employing an on-chip network in a manycore system (to improve scalability) makes the latencies of the data accesses issued by a core non-uniform. This non-uniformity can play a significant role in shaping the overall application performance. This work presents a novel compiler strategy which involves exposing architecture information to the compiler to enable an optimized computation-to-core mapping. Specifically, we propose a compiler-guided scheme that takes into account the relative positions of (and distances between) cores, last-level caches (LLCs) and memory controllers (MCs) in a manycore system, and generates a mapping of computations to cores with the goal of minimizing the on-chip network traffic. The experimental data collected using a set of 21 multi-threaded applications reveal that, on an average, our approach reduces the on-chip network latency in a 6×6 manycore system by 38.4% in the case of private LLCs, and 43.8% in the case of shared LLCs. These improvements translate to the corresponding execution time improvements of 10.9% and 12.7% for the private LLC and shared LLC based systems, respectively.-
dc.languageEnglish-
dc.publisherAssociation for Computing Machinery-
dc.titleEnhancing computation-to-core assignment with physical location information-
dc.typeConference-
dc.identifier.wosid000452469600022-
dc.identifier.scopusid2-s2.0-85049567574-
dc.type.rimsCONF-
dc.citation.beginningpage312-
dc.citation.endingpage327-
dc.citation.publicationname39th ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2018-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationPhiladelphia, PA-
dc.identifier.doi10.1145/3192366.3192386-
dc.contributor.localauthorJung, Myoungsoo-
dc.contributor.nonIdAuthorKislal, Orhan-
dc.contributor.nonIdAuthorKotra, Jagadish-
dc.contributor.nonIdAuthorTang, Xulong-
dc.contributor.nonIdAuthorKandemir, Mahmut Taylan-
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EE-Conference Papers(학술회의논문)
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