ASPS-3.5
RATE CODING OR DIRECT CODING: WHICH ONE IS BETTER FOR ACCURATE, ROBUST, AND ENERGY-EFFICIENT SPIKING NEURAL NETWORKS?
Youngeun Kim, Hyoungseob Park, Abhishek Moitra, Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Priyadarshini Panda, Yale University, United States of America
Session:
Signal Processing, Machine Learning, and Architecture Design Optimization
Track:
Applied Signal Processing Systems
Location:
Gather Area A
Presentation Time:
Tue, 10 May, 23:00 - 23:45 China Time (UTC +8)
Tue, 10 May, 15:00 - 15:45 UTC
Tue, 10 May, 15:00 - 15:45 UTC
Session Chair:
Li Liu, Chinese University of Hong Kong (SZ)
Session ASPS-3
ASPS-3.1: AN EFFICIENT METHOD FOR GENERIC DSP IMPLEMENTATION OF DILATED CONVOLUTION
Harinarayanan EV, Sachin Ghanekar, Cadence Design Systems, India
ASPS-3.2: COMPRESSION-AWARE PROJECTION WITH GREEDY DIMENSION REDUCTION FOR CONVOLUTIONAL NEURAL NETWORK ACTIVATIONS
Yu-Shan Tai, Chieh-Fang Teng, Cheng-Yang Chang, An-Yeu Wu, National Taiwan University, Taiwan
ASPS-3.3: OPTIMIZING THE CONSUMPTION OF SPIKING NEURAL NETWORKS WITH ACTIVITY REGULARIZATION
Simon Narduzzi, Siavash A. Bigdeli, L. Andrea Dunbar, Centre suisse d'électronique et de microtechnique, Switzerland; Shih-Chii Liu, University of Zürich, Switzerland
ASPS-3.4: IMPQ: REDUCED COMPLEXITY NEURAL NETWORKS VIA GRANULAR PRECISION ASSIGNMENT
Sujan Kumar Gonugondla, Amazon, United States of America; Naresh Shanbhag, University of Illinois at Urbana-Champaign, United States of America
ASPS-3.5: RATE CODING OR DIRECT CODING: WHICH ONE IS BETTER FOR ACCURATE, ROBUST, AND ENERGY-EFFICIENT SPIKING NEURAL NETWORKS?
Youngeun Kim, Hyoungseob Park, Abhishek Moitra, Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Priyadarshini Panda, Yale University, United States of America
ASPS-3.6: PYXIS: AN OPEN-SOURCE PERFORMANCE DATASET OF SPARSE ACCELERATORS
Linghao Song, Yuze Chi, Jason Cong, University of California, Los Angeles, United States of America