The impact of on-chip communication on memory technologies for neuromorphic systems

被引:15
|
作者
Moradi, Saber [1 ]
Manohar, Rajit [1 ]
机构
[1] Yale Univ, Sch Engn & Appl Sci, Comp Syst Lab, New Haven, CT 06520 USA
关键词
on-chip communication; emergent memory; memristor; neuromorphic; routing architecture; nanoscale; power consumption; SILICON; NETWORK; DESIGN; MODEL; ARCHITECTURE; PROCESSOR;
D O I
10.1088/1361-6463/aae641
中图分类号
O59 [应用物理学];
学科分类号
摘要
Emergent nanoscale non-volatile memory technologies with high integration density offer a promising solution to overcome the scalability limitations of CMOS-based neural networks architectures, by efficiently exhibiting the key principle of neural computation. Despite the potential improvements in computational costs, designing high-performance on-chip communication networks that support flexible, large-fanout connectivity remains as daunting task. In this paper, we elaborate on the communication requirements of large-scale neuromorphic designs, and point out the differences with the conventional network-on-chip architectures. We present existing approaches for on-chip neuromorphic routing networks, and discuss how new memory and integration technologies may help to alleviate the communication issues in constructing next-generation intelligent computing machines.
引用
收藏
页数:11
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