597 citations · 4.3k across the 121 of their papers we have counts for
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cs.ET2019★ 21 cited
X-CHANGR: Changing Memristive Crossbar Mapping for Mitigating Line-Resistance Induced Accuracy Degradation in Deep Neural Networks
Amogh Agrawal, Chankyu Lee, Kaushik Roy
There is widespread interest in emerging technologies, especially resistive crossbars for accelerating Deep Neural Networks (DNNs). Resistive crossbars offer a highly-parallel and…
cs.ET2019★ 25 cited
PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference
Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti +8
Memristor crossbars are circuits capable of performing analog matrix-vector multiplications, overcoming the fundamental energy efficiency limitations of digital logic. They have be…