Marchisio, A., & Shafique, M. (2023). Embedded Neuromorphic Using Intel’s Loihi Processor. In S. Pasricha & M. Shafique (Eds.), Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing : Use Cases and Emerging Challenges (pp. 137–172). Springer. https://doi.org/10.1007/978-3-031-39932-9_6
Recently, spiking neural networks (SNNs) have demonstrated great success due to their high-performance and low-energy consumption, which makes them suitable for being implemented on embedded devices, such as neuromorphic chips. This chapter presents an overview of event-based SNNs on neuromorphic hardware and their applications. It provides outlooks on the neuromorphic computing platforms, with a special focus on the Intel Loihi research chip. Afterward, a case study on a “car vs. background” classifier implemented on Loihi is discussed in detail.
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Research Areas:
Computer Engineering and Software-Intensive Systems: 100%
