  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.
