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Relational algorithms for multi-bulk-synchronous processors

Published: 23 February 2013 Publication History

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.
[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.

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  • (2017)Controlled Kernel Launch for Dynamic Parallelism in GPUs2017 IEEE International Symposium on High Performance Computer Architecture (HPCA)10.1109/HPCA.2017.14(649-660)Online publication date: Feb-2017
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Published In

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
  • 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

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 February 2013

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Author Tags

  1. gpgpu
  2. relational algebra

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Cited By

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  • (2022)Parallel Logic Programming: A SequelTheory and Practice of Logic Programming10.1017/S147106842200005922:6(905-973)Online publication date: 28-Mar-2022
  • (2019)Hardware-Conscious Hash-Joins on GPUs2019 IEEE 35th International Conference on Data Engineering (ICDE)10.1109/ICDE.2019.00068(698-709)Online publication date: Apr-2019
  • (2017)Controlled Kernel Launch for Dynamic Parallelism in GPUs2017 IEEE International Symposium on High Performance Computer Architecture (HPCA)10.1109/HPCA.2017.14(649-660)Online publication date: Feb-2017
  • (2016)LaPermACM SIGARCH Computer Architecture News10.1145/3007787.300119944:3(583-595)Online publication date: 18-Jun-2016
  • (2016)General-purpose join algorithms for large graph triangle listing on heterogeneous systemsProceedings of the 9th Annual Workshop on General Purpose Processing using Graphics Processing Unit10.1145/2884045.2884054(12-21)Online publication date: 12-Mar-2016
  • (2016)LaPermProceedings of the 43rd International Symposium on Computer Architecture10.1109/ISCA.2016.57(583-595)Online publication date: 18-Jun-2016
  • (2016)Relational Learning with GPUsInternational Journal of Parallel Programming10.1007/s10766-015-0364-744:3(663-685)Online publication date: 1-Jun-2016
  • (2015)Dynamic thread block launchACM SIGARCH Computer Architecture News10.1145/2872887.275039343:3S(528-540)Online publication date: 13-Jun-2015
  • (2015)Dynamic thread block launchProceedings of the 42nd Annual International Symposium on Computer Architecture10.1145/2749469.2750393(528-540)Online publication date: 13-Jun-2015
  • (2015)Stadium HashingProceedings of the 2015 International Conference on Parallel Architecture and Compilation (PACT)10.1109/PACT.2015.13(63-74)Online publication date: 18-Oct-2015
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