GPU Adaptive In-situ Parallel Analytics (GAP)

Haoyuan Xing, Gagan Agrawal, Rajiv Ramnath

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

1 Scopus citations

Abstract

Despite the popularity of in-situ analytics in scientifc computing, there is only limited work to date on in-situ analytics for simulations running on GPUs. Notably, two unaddressed challenges are 1) performing memory-efcient in-situ analysis on accelerators and 2)automatically choosing the processing resources and suitable data representation for a given query and platform. This paper addresses both problems. First, GAP makes several new contributions toward making bitmap indices suitable, effective, and efcient as a compressed data summary structure for the GPUs this includes introducing a layout structure, a method for generating multi-attribute bitmaps, and novel techniques for bitmap-based processing of major operators that comprise complex data analytics. Second, this paper presents a performance modeling methodology, aiming to predict the placement (i.e., CPU or GPU) and the data representation choice (summarization or original) that yield the best performance on a given confguration. Our extensive evaluation of complex in-situ queries and real-world simulations shows that with our methods, analytics on GPU using bitmaps almost always outperforms other options, and the GAP performance model predicts the optimal placement and data representation for most scenarios.

Original languageEnglish (US)
Title of host publicationPACT 2022 - Proceedings of the 2022 International Conference on Parallel Architectures and Compilation Techniques
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages467-480
Number of pages14
ISBN (Electronic)9781450398688
DOIs
StatePublished - Oct 8 2022
Event31st International Conference on Parallel Architectures and Compilation Techniques, PACT 2022 - Chicago, United States
Duration: Oct 8 2022Oct 10 2022

Publication series

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

Conference

Conference31st International Conference on Parallel Architectures and Compilation Techniques, PACT 2022
Country/TerritoryUnited States
CityChicago
Period10/8/2210/10/22

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture

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