构建块计算系统的初步评价

Sayaka Terashima, Takuya Kojima, Hayate Okuhara, Kazusa Musha, H. Amano, Ryuichi Sakamoto, Masaaki Kondo, M. Namiki
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引用次数: 3

摘要

基于电感耦合芯片接口(TCI)的构建块计算系统由三维芯片堆栈组成,每个芯片堆栈都是小型专用芯片。通过改变堆叠芯片的组合,可以构建各种类型的系统。采用瑞萨65nm低漏CMOS工艺,开发了兼容MIPS R3000的处理器GeyserTT、神经网络加速器SNACC和用于构建双塔芯片SMTT的共享存储器。它们提供TCI IP(知识产权),通过将它们堆叠起来,就可以构建一个自动扶梯网络。本文给出了每个芯片的评估结果以及用RTL模拟器对其进行叠加后的性能估计。通过RTL仿真,对Alexnet部分实现时的单塔和双塔配置的性能进行了估计。评价结果表明,使用GeyserTT+SNACC的单塔结构的性能是使用GeyserTT的两倍左右。此外,使用单个真实芯片的实验结果表明,它们都以极低的功耗工作至少50MHz。双塔结构达到了单塔的2倍左右,是GeyserTT的6倍左右。单塔的耗电量约为276兆瓦,双塔的耗电量约为496兆瓦。
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A Preliminary Evaluation of Building Block Computing Systems
A building block computing system with inductive coupling Through Chip Interface (TCI) consists of 3-D chip stack, each of which is small dedicated chips. By changing the combination of stacked chips, various types of systems can be built. A MIPS R3000 compatible processor GeyserTT, a neural network accelerator SNACC and the shared memory for building the twin-tower of chips SMTT have been developed with a Renesas 65nm low leakage CMOS process. They provide the TCI IP (Intellectual Property), and an escalator network is built just by stacking them. This paper shows each chip evaluation results and performance estimation of stacking them with the RTL simulator. The performance of the single-tower and twin-tower configuration is estimated by RTL simulation when a part of Alexnet is implemented. The evaluation results showed that the single-tower configuration with GeyserTT+SNACC achieved about twice performance as the case with GeyserTT. Also, experimental results using each of the single real chip showed that all of them work at least 50MHz with extremely low power consumption. The twin-tower configuration achieved about 2x of the single-tower, that is about 6x of GeyserTT. The power consumption was about 276mW for the single-tower and 496mW for the twin-tower.
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