A Survey on Coarse-Grained Reconfigurable Architectures From a Performance Perspective

With the end of both Dennard's scaling and Moore's law, computer users and researchers are aggressively exploring alternative forms of computing in order to continue the performance scaling that we have come to enjoy. Among the more salient and practical of the post-Moore alternatives are...

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Main Authors: Artur Podobas, Kentaro Sano, Satoshi Matsuoka
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9149601/
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spelling doaj-b2f484461f274df48ae1a1ad21ef16192021-03-30T04:13:24ZengIEEEIEEE Access2169-35362020-01-01814671914674310.1109/ACCESS.2020.30120849149601A Survey on Coarse-Grained Reconfigurable Architectures From a Performance PerspectiveArtur Podobas0https://orcid.org/0000-0001-5452-6794Kentaro Sano1Satoshi Matsuoka2RIKEN Center for Computational Science, Kobe, JapanRIKEN Center for Computational Science, Kobe, JapanRIKEN Center for Computational Science, Kobe, JapanWith the end of both Dennard's scaling and Moore's law, computer users and researchers are aggressively exploring alternative forms of computing in order to continue the performance scaling that we have come to enjoy. Among the more salient and practical of the post-Moore alternatives are reconfigurable systems, with Coarse-Grained Reconfigurable Architectures (CGRAs) seemingly capable of striking a balance between performance and programmability. In this paper, we survey the landscape of CGRAs. We summarize nearly three decades of literature on the subject, with a particular focus on the premise behind the different CGRAs and how they have evolved. Next, we compile metrics of available CGRAs and analyze their performance properties in order to understand and discover knowledge gaps and opportunities for future CGRA research specialized towards High-Performance Computing (HPC). We find that there are ample opportunities for future research on CGRAs, in particular with respect to size, functionality, support for parallel programming models, and to evaluate more complex applications.https://ieeexplore.ieee.org/document/9149601/Coarse-grained reconfigurable architecturesCGRAFPGAcomputing trendsreconfigurable systemshigh-performance computing
collection DOAJ
language English
format Article
sources DOAJ
author Artur Podobas
Kentaro Sano
Satoshi Matsuoka
spellingShingle Artur Podobas
Kentaro Sano
Satoshi Matsuoka
A Survey on Coarse-Grained Reconfigurable Architectures From a Performance Perspective
IEEE Access
Coarse-grained reconfigurable architectures
CGRA
FPGA
computing trends
reconfigurable systems
high-performance computing
author_facet Artur Podobas
Kentaro Sano
Satoshi Matsuoka
author_sort Artur Podobas
title A Survey on Coarse-Grained Reconfigurable Architectures From a Performance Perspective
title_short A Survey on Coarse-Grained Reconfigurable Architectures From a Performance Perspective
title_full A Survey on Coarse-Grained Reconfigurable Architectures From a Performance Perspective
title_fullStr A Survey on Coarse-Grained Reconfigurable Architectures From a Performance Perspective
title_full_unstemmed A Survey on Coarse-Grained Reconfigurable Architectures From a Performance Perspective
title_sort survey on coarse-grained reconfigurable architectures from a performance perspective
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description With the end of both Dennard's scaling and Moore's law, computer users and researchers are aggressively exploring alternative forms of computing in order to continue the performance scaling that we have come to enjoy. Among the more salient and practical of the post-Moore alternatives are reconfigurable systems, with Coarse-Grained Reconfigurable Architectures (CGRAs) seemingly capable of striking a balance between performance and programmability. In this paper, we survey the landscape of CGRAs. We summarize nearly three decades of literature on the subject, with a particular focus on the premise behind the different CGRAs and how they have evolved. Next, we compile metrics of available CGRAs and analyze their performance properties in order to understand and discover knowledge gaps and opportunities for future CGRA research specialized towards High-Performance Computing (HPC). We find that there are ample opportunities for future research on CGRAs, in particular with respect to size, functionality, support for parallel programming models, and to evaluate more complex applications.
topic Coarse-grained reconfigurable architectures
CGRA
FPGA
computing trends
reconfigurable systems
high-performance computing
url https://ieeexplore.ieee.org/document/9149601/
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