Using Spin-Hall MTJs to Build an Energy-Efficient In-memory Computation Platform
Using Spin-Hall MTJs to Build an Energy-Efficient In-memory Computation Platform
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使用 Spin-Hall MTJ 构建节能内存计算平台
DOI：
10.1109/isqed.2019.8697377
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
S. Sapatnekar
中科院分区：
文献类型：
--
作者：
Masoud Zabihi;Zhengyang Zhao;D. Mahendra;Z. Chowdhury;Salonik Resch;Thomas J. Peterson;Ulya R. Karpuzcu;Jianping Wang;S. Sapatnekar
我们提出了自旋霍尔效应（SHE）计算随机存取存储器（CRAM）的内存计算，将考虑在设备，门，和功能水平。对于两个特定的应用（2-D卷积和神经形态数字识别），我们表明SHE-CRAM比之前基于STT的CRAM实现快3倍，能耗低4倍以上，比最先进的近存储器处理快2000倍以上，能效至少高130倍。
We present the Spin Hall Effect (SHE) Computational Random Access Memory (CRAM) for in-memory computation, incorporating considerations at the device, gate, and functional levels. For two specific applications (2-D convolution and neuromorphic digit recognition), we show that SHE-CRAM is 3x faster and has over 4x lower energy than a prior STT-based CRAM implementation, and is over 2000x faster and at least 130x more energy-efficient than state-of-the-art near-memory processing.
影响因子：
2.3
作者：
Chowdhury, Zamshed;Harms, Jonathan D.;Wang, Jian-Ping
通讯作者：
Wang, Jian-Ping