LASER: A hardware/software approach to accelerate complicated loops on CGRAs

Mahesh Balasubramanian, Shail Dave, Aviral Shrivastava, Reiley Jeyapaul

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

2 Scopus citations

Abstract

Coarse-Grained Reconfigurable Arrays (CGRAs) are popular accelerators predominantly used in streaming, filtering, and decoding applications. Due to their high performance and high power-efficiency, CGRAs can be a promising solution to accelerate the loops of general purpose applications also. However, the loops in general purpose applications are often complicated, like loops with perfect and imperfect nests and loops with nested if-then-else's (conditionals). We argue that the existing hardware-software solutions to execute branches and conditions are inefficient. In order to efficiently execute complicated loops on CGRAs, we present a hardware-software hybrid solution: LASER - a comprehensive technique to accelerate compute-intensive loops of applications. In LASER, compiler transforms complex loops, maps them to the CGRA, and lays them out in the memory in a specific manner, such that the hardware can fetch and execute the instructions from the right path at runtime. LASER achieves a geomean performance improvement of 40.91% and utilization of 43.43% with 46% lower energy consumption.

Original languageEnglish (US)
Title of host publicationProceedings of the 2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1069-1074
Number of pages6
Volume2018-January
ISBN (Electronic)9783981926316
DOIs
StatePublished - Apr 19 2018
Event2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018 - Dresden, Germany
Duration: Mar 19 2018Mar 23 2018

Other

Other2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018
CountryGermany
CityDresden
Period3/19/183/23/18

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Hardware and Architecture
  • Software
  • Information Systems and Management

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  • Cite this

    Balasubramanian, M., Dave, S., Shrivastava, A., & Jeyapaul, R. (2018). LASER: A hardware/software approach to accelerate complicated loops on CGRAs. In Proceedings of the 2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018 (Vol. 2018-January, pp. 1069-1074). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/DATE.2018.8342170