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Maximum Performance Computing with Dataflow Engines

Published: 01 July 2012 Publication History

Abstract

Multidisciplinary dataflow computing is a powerful approach to scientific computing that has led to orders-of-magnitude performance improvements for a wide range of applications.

Cited By

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  • (2023)On the RTL Implementation of FINN Matrix Vector UnitACM Transactions on Embedded Computing Systems10.1145/354714122:6(1-27)Online publication date: 9-Nov-2023
  • (2021)MC-DeFACM Transactions on Architecture and Code Optimization10.1145/344797018:3(1-25)Online publication date: 14-Apr-2021
  • (2020)UNILOGICACM Transactions on Reconfigurable Technology and Systems10.1145/340911513:4(1-32)Online publication date: 9-Sep-2020
  • Show More Cited By

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Information & Contributors

Information

Published In

cover image Computing in Science and Engineering
Computing in Science and Engineering  Volume 14, Issue 4
July 2012
101 pages

Publisher

IEEE Educational Activities Department

United States

Publication History

Published: 01 July 2012

Author Tags

  1. Computational algorithms
  2. Computational modeling
  3. Computer architecture
  4. Data processing
  5. Scientific computing
  6. computational science
  7. computer architectures
  8. dataflow computing
  9. exascale processing
  10. scientific computing

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Cited By

View all
  • (2023)On the RTL Implementation of FINN Matrix Vector UnitACM Transactions on Embedded Computing Systems10.1145/354714122:6(1-27)Online publication date: 9-Nov-2023
  • (2021)MC-DeFACM Transactions on Architecture and Code Optimization10.1145/344797018:3(1-25)Online publication date: 14-Apr-2021
  • (2020)UNILOGICACM Transactions on Reconfigurable Technology and Systems10.1145/340911513:4(1-32)Online publication date: 9-Sep-2020
  • (2020)The Compiler of DFC: A Source Code Converter that Transform the Dataflow Code to the Multi-threaded C CodeParallel and Distributed Computing, Applications and Technologies10.1007/978-3-030-69244-5_16(185-197)Online publication date: 28-Dec-2020
  • (2020)A CGRA Definition Framework for Dataflow ApplicationsApplied Reconfigurable Computing. Architectures, Tools, and Applications10.1007/978-3-030-44534-8_21(271-287)Online publication date: 1-Apr-2020
  • (2019)Automatic Pipelining and Vectorization of Scientific Code for FPGAsInternational Journal of Reconfigurable Computing10.1155/2019/73480132019Online publication date: 18-Nov-2019
  • (2019)Type-Driven Automated Program Transformations and Cost Modelling for Optimising Streaming Programs on FPGAsInternational Journal of Parallel Programming10.1007/s10766-018-0572-z47:1(114-136)Online publication date: 1-Feb-2019
  • (2018)DARSAProceedings of the 18th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation10.1145/3229631.3229644(65-72)Online publication date: 15-Jul-2018
  • (2018)A decoupled access-execute architecture for reconfigurable acceleratorsProceedings of the 15th ACM International Conference on Computing Frontiers10.1145/3203217.3203267(244-247)Online publication date: 8-May-2018
  • (2017)Efficient Branch and Bound on FPGAs Using Work Stealing and Instance-Specific DesignsACM Transactions on Reconfigurable Technology and Systems10.1145/305368710:3(1-23)Online publication date: 27-Jun-2017
  • Show More Cited By

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