Quantifying and optimizing data access parallelism on manycores

Jihyun Ryoo, Orhan Kislal, Xulong Tang, Mahmut T. Kandemir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Data access parallelism (DAP) indicates how well available hardware resources are utilized by data accesses. This paper investigates four complementary components of data access parallelism in detail: cache-level parallelism (CLP), bank-level parallelism (BLP), network-level parallelism (NLP), and memory controller-level parallelism (MLP). Specifically, we first quantify these four components for a set of 20 multi-Threaded benchmark programs, and show that, when executed on a state-of-The-Art manycore platform, their original values are quite low compared to the maximum possible values they could take. We next perform a limit study, which indicates that significant performance improvements are possible if the values of these four components of DAP could be maximized. Building upon our observations from this limit study, we then present two practical computation and network access scheduling schemes. Both these schemes make use of profile data, but, while the compiler-based strategy uses fixed priorities of CLP, BLP, NLP, and MLP, the machine learning-based one employs a predictive machine learning model. Our experiments indicate 30.8% and 36.9% performance improvements with the compiler-based and learning-based schemes, respectively. Our results also show that the proposed schemes consistently achieve significant improvements under different values of the major experimental parameters.

Original languageEnglish (US)
Title of host publicationProceedings - 26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages131-144
Number of pages14
ISBN (Electronic)9781538668863
DOIs
StatePublished - Nov 7 2018
Event26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018 - Milwaukee, United States
Duration: Sep 25 2018Sep 28 2018

Publication series

NameProceedings - 26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018

Other

Other26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018
CountryUnited States
CityMilwaukee
Period9/25/189/28/18

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Modeling and Simulation

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