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

B. Adhi, Carlos Cortes, Y. Tan, Takuya Kojima, Artur Podobas, K. Sano
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引用次数: 5

Abstract

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.
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靶向HPC的可合成CGRAs探索框架:初步设计与评价
在高性能计算(HPC)中继续进行性能扩展的更突出的加速器技术是粗粒度可重构阵列(CGRAs)。然而,CGRAs将给高性能计算工作负载带来什么好处,以及如何实现这些好处,目前仍是一个悬而未决的研究问题。在这项工作中,我们提出了一个框架来探索HPC工作负载的CGRA设计空间,其中包括一个编译和仿真工具流,一个用SystemVerilog编写的CGRA HDL库,以及一个可合成的CGRA设计作为基线。使用RTL模拟,我们用基线CGRA对多个不同架构参数的两个知名计算内核进行了评估。仿真结果验证了该勘探框架的正确性和有效性。
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