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A Parallel SystemC Virtual Platform for Neuromorphic Architectures

Lookup NU author(s): Dr Farhad Merchant

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Abstract

With the increasing interest in neuromorphic computing, designers of embedded systems face the challenge of efficiently simulating such platforms to enable architecture design exploration early in the development cycle. Executing artificial neural network applications on neuromorphic systems which are being simulated on virtual platforms (VPs) is an extremely demanding computational task. Nevertheless, it is a vital benchmarking task for comparing different possible architectures. Therefore, exploiting the multicore capabilities of the VP’s host system is essential to achieve faster simulations. Hence, this paper presents a parallel SystemC based VP for RISC-V multicore platforms integrating multiple computing-in-memory neuromorphic accelerators. In this paper, different VP segmentation architectures are explored for the integration of neuromorphic accelerators and are shown their corresponding speedup simulations compared to conventional sequential SystemC execution.


Publication metadata

Author(s): Galicia M, Merchant F, Leupers R

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 23rd International Symposium on Quality Electronic Design (ISQED)

Year of Conference: 2022

Online publication date: 29/06/2022

Acceptance date: 01/03/2022

Publisher: Institute of Electrical and Electronics Engineers

URL: https://doi.org/10.1109/ISQED54688.2022.9806235

DOI: 10.1109/ISQED54688.2022.9806235

Notes: BEST PAPER AWARDED

Library holdings: Search Newcastle University Library for this item

ISBN: 9781665494670


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