@inproceedings{f41a88a7518444779a35564af2e33aad,
title = "SENSIM: An Event-driven Parallel Simulator for Multi-core Neuromorphic Systems",
abstract = "In this paper, we present SENSIM, which is an open-source simulator designed specifically for the SENECA neuromorphic processor. This simulator is unique in that it combines features from both hardware-specific and hardware-agnostic spiking neural network simulators, resulting in a hybrid event-driven and time-step-driven simulation approach. This allows for flexibility between accuracy and speed during different stages of simulation. Our work highlights the open-source SENSIM platform, which enables the mapping of large-scale SNN/DNN models to the SENECA cores, as well as the benchmarking of crucial KPIs such as power and latency estimations. Source code of the simulator can be found in https://github.com/Prithvish04/SENSIM-paper-submission.",
keywords = "2025 OA procedure, Neuromorphic, SENECA, SENSIM, SNN/DNN inference, Hardware-aware Simulation",
author = "Prithvish Nembhani and Kanishkan Vadivel and Guangzhi Tang and Mohammad Tahghighi and \{Van Schaik\}, \{Gert Jan\} and Manolis Sifalakis and Zaid Al-Ars and Amirreza Yousefzadeh",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; International Joint Conference on Neural Networks, IJCNN 2024, IJCNN 2024 ; Conference date: 30-06-2024 Through 05-07-2024",
year = "2024",
doi = "10.1109/IJCNN60899.2024.10651400",
language = "English",
isbn = "979-8-3503-5932-9",
series = "Proceedings of the International Joint Conference on Neural Networks (IJCNN)",
publisher = "IEEE",
booktitle = "2024 International Joint Conference on Neural Networks, IJCNN 2024 - Proceedings",
address = "United States",
}