Efficient FPGA implementations of pair and triplet-based STDP for neuromorphic architectures

Lammie, Corey, Hamilton, Tara Julia, van Schaik, André, and Rahimi Azghadi, Mostafa (2019) Efficient FPGA implementations of pair and triplet-based STDP for neuromorphic architectures. IEEE Transactions on Circuits and Systems I: Regular Papers, 66 (4). pp. 1558-1570.

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Abstract

Synaptic plasticity is envisioned to bring about learning and memory in the brain. Various plasticity rules have been proposed, among which spike-timing-dependent plasticity (STDP) has gained the highest interest across various neural disciplines, including neuromorphic engineering. Here, we propose highly efficient digital implementations of pair-based STDP (PSTDP) and triplet-based STDP (TSTDP) on field programmable gate arrays that do not require dedicated floating-point multipliers and hence need minimal hardware resources. The implementations are verified by using them to replicate a set of complex experimental data, including those from pair, triplet, quadruplet, frequency-dependent pairing, as well as Bienenstock-Cooper-Munro experiments. We demonstrate that the proposed TSTDP design has a higher operating frequency that leads to 2.46x faster weight adaptation (learning) and achieves 11.55 folds improvement in resource usage, compared to a recent implementation of a calcium-based plasticity rule capable of exhibiting similar learning performance. In addition, we show that the proposed PSTDP and TSTDP designs, respectively, consume 2.38x and 1.78x less resources than the most efficient PSTDP implementation in the literature. As a direct result of the efficiency and powerful synaptic capabilities of the proposed learning modules, they could be integrated into large-scale digital neuromorphic architectures to enable high-performance STDP learning.

Item ID: 56547
Item Type: Article (Research - C1)
ISSN: 1558-0806
Keywords: STDP; neuromorphic engineering; Hebbian learning; FPGA; synaptic plasticity
Copyright Information: Copyright © 2018 IEEE.
Date Deposited: 18 Dec 2018 01:34
FoR Codes: 40 ENGINEERING > 4008 Electrical engineering > 400801 Circuits and systems @ 75%
40 ENGINEERING > 4009 Electronics, sensors and digital hardware > 400902 Digital electronic devices @ 25%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970109 Expanding Knowledge in Engineering @ 50%
97 EXPANDING KNOWLEDGE > 970110 Expanding Knowledge in Technology @ 50%
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