Exploration Framework for Synthesizable CGRAs Targeting HPC: Initial Design and EvaluationShow others and affiliations
2022 (English)In: 2022 IEEE 36Th International Parallel And Distributed Processing Symposium Workshops (IPDPSW 2022), Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 639-646Conference paper, Published paper (Refereed)
Abstract [en]
Among the more salient accelerator technologies to continue performance scaling in High-Performance Computing (HPC) are Coarse-Grained Reconfigurable Arrays (CGRAs). However, what benefits CGRAs will bring to HPC workloads and how those benefits will be reaped is an open research question today. In this work, we propose a framework to explore the design space of CGRAs for HPC workloads, which includes a tool flow of compilation and simulation, a CGRA HDL library written in SystemVerilog, and a synthesizable CGRA design as a baseline. Using RTL simulation, we evaluate two well-known computation kernels with the baseline CGRA for multiple different architectural parameters. The simulation results demonstrate both correctness and usefulness of our exploration framework.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022. p. 639-646
Series
IEEE International Symposium on Parallel and Distributed Processing Workshops, ISSN 2164-7062
Keywords [en]
CGRA, Framework, Design space exploration, HPC, RTL simulation, OpenMP
National Category
Computer Engineering Computer Sciences Building Technologies
Identifiers
URN: urn:nbn:se:kth:diva-319838DOI: 10.1109/IPDPSW55747.2022.00113ISI: 000855041000080Scopus ID: 2-s2.0-85136163074OAI: oai:DiVA.org:kth-319838DiVA, id: diva2:1702622
Conference
36th IEEE International Parallel and Distributed Processing Symposium (IEEE IPDPS), MAY 30-JUN 03, 2022, ELECTR NETWORK
Note
QC 20221011
2022-10-112022-10-112022-10-11Bibliographically approved