Browse by author
Lookup NU author(s): Dr Farhad Merchant
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
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.
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