The tutorial will be held on Friday April 26 at the Neuro-Inspired Computational Elements 2024 Conference titled “Neuromorphic Intermediate Representation“.
Monthly Archives: March 2024
New Paper: “Optically Tunable Electrical Oscillations in Oxide-Based Memristors for Neuromorphic Computing” led by Collaborator Dr. Shimul K. Nath
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New snnTorch Tutorial: Spiking-Tactile MNIST by Undergraduate Students Dylan Louie, Hannah Cohen-Sandler, and Shatoparba Banerjee
See the tutorial here.
The next tutorial from UCSC’s Brain-Inspired Machine Learning class is by Dylan J. Louie, Hannah Cohen Sandler and Shatoparba Banerjee.
They show how to train an SNN for tactile sensing using the Spiking-Tactile MNIST Neuromorphic Dataset. This dataset was developed in Benjamin C.K. Tee‘s lab in NUS. It consists of handwritten digits obtained by human participants writing on a neuromorphic tactile sensor array.
For more information about the dataset, see the preprint by Hian Hian See et al. here.
Prof. Jason Eshraghian and Dr. Fabrizio Ottati Present Tutorial at ISFPGA (Monterey, CA)
Fabrizio Ottati and I will be running a tutorial tomorrow (Sunday, 3 March) at the International Symposium on Field-Programmable Gate Arrays (ISFPGA) in Monterey, CA titled: “Who needs neuromorphic hardware? Deploying SNNs to FPGAs via HLS”.
We’ll go through software and hardware: training SNNs using quantization-aware techniques across weights and stateful quantization, and then show how to go from an snnTorch model straight into AMD/Xilinx FPGAs for low-power + flexible deployment.
GitHub repo: https://github.com/open-neuromorphic/fpga-snntorch
Tutorial summary: https://www.isfpga.org/workshops-tutorials/#t2