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CGRA-EAM—Rapid Energy and Area Estimation for Coarse-grained Reconfigurable Architectures

Authors:

Mark Wijtvliet,

Henk Corporaal,

Akash KumarAuthors Info & Claims

ACM Transactions on Reconfigurable Technology and Systems (TRETS), Volume 14, Issue 4

Article No.: 19, Pages 1 - 28

https://doi.org/10.1145/3468874

Published: 13 September 2021 Publication History

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Abstract

Reconfigurable architectures are quickly gaining in popularity due to their flexibility and ability to provide high energy efficiency. However, reconfigurable systems allow for a huge design space. Iterative design space exploration (DSE) is often required to achieve good Pareto points with respect to some combination of performance, area, and/or energy. DSE tools depend on information about hardware characteristics in these aspects. These characteristics can be obtained from hardware synthesis and net-list simulation, but this is very time-consuming. Therefore, architecture models are common. This work introduces CGRA-EAM (Coarse-Grained Reconfigurable Architecture - Energy & Area Model), a model for energy and area estimation framework for coarse-grained reconfigurable architectures. The model is evaluated for the Blocks CGRA. The results demonstrate that the mean absolute percentage error is 15.5% and 2.1% for energy and area, respectively, while the model achieves a speedup of close to three orders of magnitude compared to synthesis.

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Cited By

de Bruin BVadivel KWijtvliet MJääskeläinen PCorporaal H(2024)R-Blocks: an Energy-Efficient, Flexible, and Programmable CGRAACM Transactions on Reconfigurable Technology and Systems10.1145/365664217:2(1-34)Online publication date: 10-May-2024
https://dl.acm.org/doi/10.1145/3656642
Ebrahimi ZKumar A(2024)GREEN: An Approximate SIMD/MIMD CGRA for Energy-Efficient Processing at the EdgeIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2024.338334943:10(2874-2887)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1109/TCAD.2024.3383349
Shi CAdhi BMiwa SSano K(2024)Post-Route Power Estimation: A Case Study of RIKEN-CGRA2024 IEEE International Conference on Cluster Computing Workshops (CLUSTER Workshops)10.1109/CLUSTERWorkshops61563.2024.00041(166-167)Online publication date: 24-Sep-2024
https://doi.org/10.1109/CLUSTERWorkshops61563.2024.00041
Show More Cited By

Index Terms

CGRA-EAM—Rapid Energy and Area Estimation for Coarse-grained Reconfigurable Architectures
1. Computer systems organization
  1. Architectures
    1. Other architectures
      1. Reconfigurable computing
2. Hardware
  1. Electronic design automation
    1. Modeling and parameter extraction

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Information

Published In

cover image ACM Transactions on Reconfigurable Technology and Systems

ACM Transactions on Reconfigurable Technology and Systems Volume 14, Issue 4

December 2021

165 pages

ISSN:1936-7406

EISSN:1936-7414

DOI:10.1145/3483341

Editor:
Deming Chen
University of Illinois, Urbana-Champaign Urbana, USA

Issue’s Table of Contents

Copyright © 2021 Association for Computing Machinery.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 September 2021

Accepted: 01 May 2021

Revised: 01 May 2021

Received: 01 December 2020

Published in TRETS Volume 14, Issue 4

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Cited By

de Bruin BVadivel KWijtvliet MJääskeläinen PCorporaal H(2024)R-Blocks: an Energy-Efficient, Flexible, and Programmable CGRAACM Transactions on Reconfigurable Technology and Systems10.1145/365664217:2(1-34)Online publication date: 10-May-2024
https://dl.acm.org/doi/10.1145/3656642
Ebrahimi ZKumar A(2024)GREEN: An Approximate SIMD/MIMD CGRA for Energy-Efficient Processing at the EdgeIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2024.338334943:10(2874-2887)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1109/TCAD.2024.3383349
Shi CAdhi BMiwa SSano K(2024)Post-Route Power Estimation: A Case Study of RIKEN-CGRA2024 IEEE International Conference on Cluster Computing Workshops (CLUSTER Workshops)10.1109/CLUSTERWorkshops61563.2024.00041(166-167)Online publication date: 24-Sep-2024
https://doi.org/10.1109/CLUSTERWorkshops61563.2024.00041
Yang KJiang LShan RLi KCui X(2023)RMSRM: real-time monitoring-based self-reconfiguration mechanism in reconfigurable PE arrayThe Journal of Supercomputing10.1007/s11227-023-05707-080:5(7071-7101)Online publication date: 3-Nov-2023
https://dl.acm.org/doi/10.1007/s11227-023-05707-0
Wijtvliet MCorporaal HKumar AWijtvliet MCorporaal HKumar A(2023)EinführungBlocks: Auf dem Weg zu Energieeffizienten, Grobkörnigen, Rekonfigurierbaren Architekturen (CGRA)10.1007/978-3-031-36650-5_1(1-15)Online publication date: 10-Sep-2023
https://doi.org/10.1007/978-3-031-36650-5_1
Wijtvliet MCorporaal HKumar AWijtvliet MCorporaal HKumar A(2021)IntroductionBlocks, Towards Energy-efficient, Coarse-grained Reconfigurable Architectures10.1007/978-3-030-79774-4_1(1-14)Online publication date: 5-Jun-2021
https://doi.org/10.1007/978-3-030-79774-4_1

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