Field-Programmable Crossbar Array (FPCA) for Reconfigurable Computing

被引:19
|
作者
Zidan, Mohammed A. [1 ]
Jeong, YeonJoo [1 ]
Shin, Jong Hoon [1 ]
Du, Chao [1 ]
Zhang, Zhengya [1 ]
Lu, Wei D. [1 ]
机构
[1] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
来源
IEEE TRANSACTIONS ON MULTI-SCALE COMPUTING SYSTEMS | 2018年 / 4卷 / 04期
基金
美国国家科学基金会;
关键词
Cognitive computing; crossbar; memristor; non-von neumann; RRAM;
D O I
10.1109/TMSCS.2017.2721160
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For decades, advances in electronics were directly driven by the scaling of CMOS transistors according to Moore's law. However, both the CMOS scaling and the classical computer architecture are approaching fundamental and practical limits, and new computing architectures based on emerging devices, such as resistive random-access memory (RRAM) devices, are expected to sustain the exponential growth of computing capability. Here, we propose a novel memory-centric, reconfigurable, general purpose computing platform that is capable of handling the explosive amount of data in a fast and energy-efficient manner. The proposed computing architecture is based on a uniform, physical, resistive, memory-centric fabric that can be optimally reconfigured and utilized to perform different computing and data storage tasks in a massively parallel approach. The system can be tailored to achieve maximal energy efficiency based on the data flow by dynamically allocating the basic computing fabric for storage, arithmetic, and analog computing including neuromorphic computing tasks.
引用
收藏
页码:698 / 710
页数:13
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