计算机科学
电阻随机存取存储器
逻辑门
计算机体系结构
内存处理
建筑
计算
逻辑综合
逻辑族
计算机工程
理论计算机科学
并行计算
计算机硬件
程序设计语言
算法
电压
电气工程
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作者
Minh S. Q. Truong,Liting Shen,Alexander Glass,Alison Hoffmann,L.R. Carley,James A. Bain,Saugata Ghose
标识
DOI:10.1109/jetcas.2022.3171765
摘要
Modern computing applications based upon machine learning can incur significant data movement overheads in state-of-the-art computers. Resistive-memory-based processing-using-memory (PUM) can mitigate this data movement by instead performing computation in situ (i.e., directly within memory cells), but device-level limitations restrict the practicality and/or performance of many PUM architecture proposals. The RACER architecture overcomes these limitations, by proposing efficient peripheral circuitry and the concept of bit-pipelining to enable high-performance, high-efficiency computation using small memory tiles. In this work, we extend RACER to adapt easily to different PUM logic families, by (1) modifying the device access circuitry to support a wide range of logic families, (2) evaluating three logic families proposed by prior work, and (3) proposing and evaluating a new logic family called OSCAR that significantly relaxes the switching voltage constraints required to perform logic with resistive memory devices. We show that the modified RACER architecture, using the OSCAR logic family, can enable practical PUM on real ReRAM devices while improving performance and energy savings by 30% and 37%, respectively, over the original RACER work.
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