Mapping Spiking Neural Networks to Neuromorphic Hardware

no code implementations • 4 Sep 2019 • Adarsha Balaji, Anup Das, Yuefeng Wu, Khanh Huynh, Francesco Dell'Anna, Giacomo Indiveri, Jeffrey L. Krichmar, Nikil Dutt, Siebren Schaafsma, Francky Catthoor

SpiNePlacer then finds the best placement of local and global synapses on the hardware using a meta-heuristic-based approach to minimize energy consumption and spike latency.

Clustering

Mapping of Local and Global Synapses on Spiking Neuromorphic Hardware

no code implementations • 13 Aug 2019 • Anup Das, Yuefeng Wu, Khanh Huynh, Francesco Dell'Anna, Francky Catthoor, Siebren Schaafsma

Partitioning SNNs becomes essential in order to map them on neuromorphic hardware with the major aim to reduce the global communication latency and energy overhead.

Image Classification