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Relational algorithms for multi-bulk-synchronous processors

Published:23 February 2013Publication History
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Abstract

Relational databases remain an important application infrastructure for organizing and analyzing massive volumes of data. At the same time, processor architectures are increasingly gravitating towards Multi-Bulk-Synchronous processor (Multi-BSP) architectures employing throughput-optimized memory systems, lightweight multi-threading, and Single-Instruction Multiple-Data (SIMD) core organizations. This paper explores the mapping of primitive relational algebra operations onto such architectures to improve the throughput of data warehousing applications built on relational databases.

References

  1. H. Wu, G. Diamos, S. Cadambi, and S. Yalamanchili. Kernel weaver: Automatically fusing database primitives for efficient gpu computation. In Proceedings of the 45th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO-45 '12, pages 107--118, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. G. Diamos, H. Wu, A. Lele, J. Wang, and S. Yalamanchili. Efficient relational algebra algorithms and data structures for gpu. Technical Report GIT-CERCS-12-01, CERCS, Georgia Institute of Technology, 2012.Google ScholarGoogle Scholar

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  1. Relational algorithms for multi-bulk-synchronous processors

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          • Published in

            cover image ACM SIGPLAN Notices
            ACM SIGPLAN Notices  Volume 48, Issue 8
            PPoPP '13
            August 2013
            309 pages
            ISSN:0362-1340
            EISSN:1558-1160
            DOI:10.1145/2517327
            Issue’s Table of Contents
            • cover image ACM Conferences
              PPoPP '13: Proceedings of the 18th ACM SIGPLAN symposium on Principles and practice of parallel programming
              February 2013
              332 pages
              ISBN:9781450319225
              DOI:10.1145/2442516

            Copyright © 2013 Authors

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 23 February 2013

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