Experiences with ML-Driven Design: A NoC Case Study

Experiences with ML-Driven Design: A NoC Case Study
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机器学习驱动设计的经验:NoC 案例研究

DOI:
10.1109/hpca47549.2020.00058
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发表时间:
2020
期刊:
2020 IEEE International Symposium on High Performance Computer Architecture (HPCA)
影响因子:
--
通讯作者:
G. Loh
G. Loh
中科院分区:
--
文献类型:
--
作者:
Jieming Yin;Subhash Sethumurugan;Yasuko Eckert;Chintan Patel;Alan Smith;Eric Morton;M. Oskin;Natalie D. Enright Jerger;G. Loh

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最近,人们对将机器学习(ML)应用于系统设计产生了很大的兴趣,它旨在帮助人类专家提取新的见解,从而获得更好的系统。在这项工作中,我们分享了我们应用ML来改进片上网络(NoC)的一个方面的经验,以发现新的想法和方法,这最终使我们找到了一种新的仲裁方案,该方案对竞争激烈的NoC有效。然而,仍然需要大量的人力和创造力来优化整个处理器的一个组件(NoC)的一个方面(仲裁)。这使我们得出结论,许多工作(和机会!)在ML驱动的架构设计领域仍有待完成。
There has been a lot of recent interest in applying machine learning (ML) to the design of systems, which purports to aid human experts in extracting new insights leading to better systems. In this work, we share our experiences with applying ML to improve one aspect of networks-on-chips (NoC) to uncover new ideas and approaches, which eventually led us to a new arbitration scheme that is effective for NoCs under heavy contention. However, a significant amount of human effort and creativity was still needed to optimize just one aspect (arbitration) of what is only one component (the NoC) of the overall processor. This leads us to conclude that much work (and opportunity!) remains to be done in the area of ML-driven architecture design.
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发表时间: 2016
期刊: 2016 49th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO
影响因子: --
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