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.
翻译:随着对神经形态计算的兴趣日益浓厚,嵌入系统的设计者面临着有效模拟这些平台的挑战,以便在开发周期的早期阶段就能够进行建筑设计探索。在虚拟平台上模拟的神经形态系统中执行人造神经网络应用是一项极为艰巨的计算任务。然而,这是比较不同可能的结构的一项至关重要的基准任务。因此,开发VP主机系统的多核心能力对于实现更快的模拟至关重要。因此,本文件为融合多种计算机-分子神经形态加速器的RISC-V多核心平台提供了一个平行的基于系统C的VP。在本文件中,为神经形态加速器的整合探索了不同的VP分割结构,并展示了它们与常规的 Syc 执行相对应的加速模拟。