DL-RSIM: a simulation framework to enable reliable ReRAM-based accelerators for deep learning

Meng-Yao Lin
Meng-Yao Lin
Wei-Ting Lin
Wei-Ting Lin
Tzu-Hsien Yang
Tzu-Hsien Yang
I-Ching Tseng
I-Ching Tseng
Han-Wen Hu
Han-Wen Hu
Meng-Fan Chang
Meng-Fan Chang

ICCAD '18: IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN San Diego California November, 2018, pp. 1-8, 2018.

Cited by: 9|Bibtex|Views8
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Other Links: dl.acm.org

Abstract:

Memristor-based deep learning accelerators provide a promising solution to improve the energy efficiency of neuromorphic computing systems. However, the electrical properties and crossbar structure of memristors make these accelerators error-prone. To enable reliable memristor-based accelerators, a simulation platform is needed to precise...More

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