Legion-based scientific data analytics on heterogeneous processors

Lina Yu, Hongfeng Yu

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

Abstract

We present a study of scientific data analytics on heterogeneous architectures using the Legion runtime system. Legion is a new programming model and runtime system targeting distributed heterogeneous architectures. It introduces logical regions as a new abstraction for describing the structures and usages of program data. We describe how to leverage logical regions to express important properties of program data, such as locality and independence, for scientific data analytics that can consist of multiple operations with different data types. Our approach can help users simplify programming on the data partition, data organization, and data movement for distributed-memory heterogeneous architectures, thereby facilitating a simultaneous execution of multiple analytics operations on modern and future supercomputers. We demonstrate the scalability and the usability of our approach by a hybrid data partitioning and distribution scheme for different data types using both CPUs and GPUs on a heterogeneous system.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE International Conference on Big Data, Big Data 2016
EditorsRonay Ak, George Karypis, Yinglong Xia, Xiaohua Tony Hu, Philip S. Yu, James Joshi, Lyle Ungar, Ling Liu, Aki-Hiro Sato, Toyotaro Suzumura, Sudarsan Rachuri, Rama Govindaraju, Weijia Xu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2305-2314
Number of pages10
ISBN (Electronic)9781467390040
DOIs
StatePublished - Jan 1 2016
Event4th IEEE International Conference on Big Data, Big Data 2016 - Washington, United States
Duration: Dec 5 2016Dec 8 2016

Publication series

NameProceedings - 2016 IEEE International Conference on Big Data, Big Data 2016

Other

Other4th IEEE International Conference on Big Data, Big Data 2016
CountryUnited States
CityWashington
Period12/5/1612/8/16

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Keywords

  • Legion
  • heterogeneous processors
  • scientific data analytics

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Hardware and Architecture

Cite this

Yu, L., & Yu, H. (2016). Legion-based scientific data analytics on heterogeneous processors. In R. Ak, G. Karypis, Y. Xia, X. T. Hu, P. S. Yu, J. Joshi, L. Ungar, L. Liu, A-H. Sato, T. Suzumura, S. Rachuri, R. Govindaraju, & W. Xu (Eds.), Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016 (pp. 2305-2314). [7840863] (Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2016.7840863