Task 004: Neural Primitives
Event Date: | May 7, 2020 |
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Priority: | No |
School or Program: | Electrical and Computer Engineering |
College Calendar: | Show |
Enhancing Robustness of ReRAM Crossbars for In-memory Architectures via data-encoding methods
Abstract:
Crossbar-based in-memory architectures have emerged as an attractive platform for energy-efficient realization of deep neural networks (DNNs). A key challenge in such architectures is achieving accurate and efficient writes due to the presence of bitcell conductance variations. In this talk, we propose the Single-Write In-memory Program-vErify (SWIPE) method that achieves high accuracy writes for crossbar-based in-memory architectures at 5×-to-10× lower cost than standard program-verify methods. SWIPE leverages the bit-sliced attribute of crossbar-based in-memory architectures and the statistics of conductance variations to compensate for device non-idealities. Using SWIPE to write into ReRAM crossbar allows for a 2× (CIFAR-10) and 3× (MNIST) increase in storage density with <1% loss in DNN accuracy. In particular, SWIPE compensates for 4.8×-to-7.7× higher conductance variations. Furthermore, SWIPE can be augmented with injection-based training methods in order to achieve even greater enhancements in robustness.
Bio:
Sujan K. Gonugondla received the Bachelor’s and Master’s in Technology degrees in Electrical Engineering from the Indian Institute of Technology Madras, Chennai, India, in 2014 and the Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign, Urbana, IL, USA in 2020. His research interests are in energy-efficient integrated circuits, and low complexity algorithms for machine learning systems, specifically algorithm hardware co-design for inference under resource-constraints.
Sujan K. Gonugondla is a recipient of the Dr. Ok Kyun Kim Fellowship 2018-19 and the M. E. Van Valkenburg Graduate Research Award 2019-20 from the ECE department at the University of Illinois at Urbana-Champaign, the ADI Outstanding Student Designer Award 2018 and the prestigious SSCS Predoctoral Achievement award in. He has received Best Student Paper Awards in International Conference on Acoustics, Speech and Signal Processing (ICASSP) in 2016, and International conference in Circuits and Systems (ISCAS) in 2018.