SEVDA: Singular Value Decomposition Based Parallel Write Scheme for Memristive CNN Accelerators
Author:
Affiliation:
1. University of Toronto,Department of Electrical and Computer Engineering,Toronto,Canada
2. York University,Department of Electrical Engineering and Computer Science,Toronto,Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10181241/10181318/10182097.pdf?arnumber=10182097
Reference21 articles.
1. Resistive Crossbars as Approximate Hardware Building Blocks for Machine Learning: Opportunities and Challenges
2. DeepId-Net: Multi-Stage and Deformable Deep Convolutional Neural Networks for Object Detection;ouyang;ArXiv Preprint,2014
3. ISAAC: A Convolutional Neural Network Accelerator with In-Situ Analog Arithmetic in Crossbars
4. PRUNIX: Non-Ideality Aware Convolutional Neural Network Pruning for Memristive Accelerators
5. VTEAM: A General Model for Voltage-Controlled Memristors
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