A 2.1 pJ/SOP 40nm SNN Accelerator Featuring On-chip Transfer Learning using Delta STDP

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A 2.1 pJ/SOP 40nm SNN Accelerator Featuring On-chip Transfer Learning using Delta STDP
Title:
A 2.1 pJ/SOP 40nm SNN Accelerator Featuring On-chip Transfer Learning using Delta STDP
Journal Title:
ESSCIRC 2021 - IEEE 47th European Solid State Circuits Conference (ESSCIRC)
Keywords:
Publication Date:
26 October 2021
Citation:
Wong, M. M., Shrestha, S. B., Nambiar, V. P., Mani, A., Lee, Y. K., Koh, E. K., … Do, A. T. (2021). A 2.1 pJ/SOP 40nm SNN Accelerator Featuring On-chip Transfer Learning using Delta STDP. ESSCIRC 2021 - IEEE 47th European Solid State Circuits Conference (ESSCIRC). doi:10.1109/esscirc53450.2021.9567782
Abstract:
This work introduces a neuromorphic chip featuring energy-efficient transfer learning capability using a new learning rule, Delta- Spike Time Dependent Plasticity (STDP). Delta STDP enables the neuromorphic chip to leverage on its previous knowledge to learn and to solve different but related tasks at a faster rate and with a limited number (few shots) of training samples. Compared to the unsupervised on-chip learning (OCL) rules, Delta STDP offers lower learning overheads as it has ~20% lower memory utilization and is operated only on the last layer of the Spiking Neural Network (SNN). A test chip fabricated in 40nm demonstrates this on-chip learning concept using DVS gesture and MNIST datasets. It achieves an accuracy of >80% for DVS gesture (using 9.8K training samples) with the total energy/learning is 5.2J at 0.5V. For MNIST, using only 2K training samples, it attains an accuracy of 97% and this learning convergence rate is >10x the conventional OCLs. The total energy/learning for MNIST dataset is 8.6mJ at 0.5V. Overall, the chip consumes 2.1 pJ/SOP at 0.5V, which is 12.3x-91.4x lower compared to the existing state-of-the-art.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the National Research Foundation Singapore - Innovation and Enterprise 2020 - Advanced Manufacturing and Engineering
Grant Reference no. : A1687b0033
Description:
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISBN:
978-1-6654-3751-6
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