Optimizing data layouts for parallel computation on multicores

Yuanrui Zhang, Wei Ding, Jun Liu, Mahmut Kandemir

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

15 Scopus citations

Abstract

The emergence of multicore platforms offers several opportunities for boosting application performance. These opportunities, which include parallelism and data locality benefits, require strong support from compilers as well as operating systems. Current compiler research targeting multicores mostly focuses on code restructuring and mapping. In this work, we explore automatic data layout transformation targeting multithreaded applications running on multicores. Our transformation considers both data access patterns exhibited by different threads of a multithreaded application and the onchip cache topology of the target multicore architecture. It automatically determines a customized memory layout for each target array to minimize potential cache conflicts across threads. Our experiments show that, our optimization brings significant benefits over state-of-the-art data locality optimization strategies when tested using 30 benchmark programs on an Intel multicore machine. The results also indicate that this strategy is able to scale to larger core counts and it performs better with increased data set sizes.

Original languageEnglish (US)
Title of host publicationProceedings - 2011 International Conference on Parallel Architectures and Compilation Techniques, PACT 2011
Pages143-154
Number of pages12
DOIs
StatePublished - Dec 1 2011
Event20th International Conference on Parallel Architectures and Compilation Techniques, PACT 2011 - Galveston, TX, United States
Duration: Oct 10 2011Oct 14 2011

Publication series

NameParallel Architectures and Compilation Techniques - Conference Proceedings, PACT
ISSN (Print)1089-795X

Other

Other20th International Conference on Parallel Architectures and Compilation Techniques, PACT 2011
CountryUnited States
CityGalveston, TX
Period10/10/1110/14/11

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture

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  • Cite this

    Zhang, Y., Ding, W., Liu, J., & Kandemir, M. (2011). Optimizing data layouts for parallel computation on multicores. In Proceedings - 2011 International Conference on Parallel Architectures and Compilation Techniques, PACT 2011 (pp. 143-154). [6113796] (Parallel Architectures and Compilation Techniques - Conference Proceedings, PACT). https://doi.org/10.1109/PACT.2011.20