Exploration Framework for Synthesizable CGRAs Targeting HPC: Initial Design and Evaluation

被引:2
作者
Adhi, Boma [1 ]
Cortes, Carlos [1 ]
Tan, Yiyu [1 ]
Kojima, Takuya [1 ,2 ]
Podobas, Artur [3 ]
Sano, Kentaro [1 ]
机构
[1] RIKEN, Ctr Computat Sci R CCS, Wako, Saitama, Japan
[2] Univ Tokyo, Grad Sch Informat Sci & Technol, Tokyo, Japan
[3] KTH Royal Inst Technol, Stockholm, Sweden
来源
2022 IEEE 36TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW 2022) | 2022年
基金
日本学术振兴会;
关键词
CGRA; Framework; Design space exploration; HPC; RTL simulation; OpenMP; ARCHITECTURE;
D O I
10.1109/IPDPSW55747.2022.00113
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:639 / 646
页数:8
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