A Parallel SystemC Virtual Platform for Neuromorphic Architectures

TL;DR

This paper introduces a parallel SystemC virtual platform for simulating neuromorphic architectures on RISC-V multicore systems, enabling faster architecture exploration and benchmarking.

Contribution

It presents a novel parallel SystemC-based virtual platform that integrates neuromorphic accelerators and explores different segmentation architectures for improved simulation speed.

Findings

Parallel execution achieves significant speedup over sequential simulation

Different VP segmentation architectures impact simulation performance

The platform facilitates efficient neuromorphic system benchmarking

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.