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Abstract
Abstract
Lava is an open-source software framework for developing neuro-inspired applications and mapping them to neuromorphic hardware. Lava provides developers with the tools and abstractions to develop applications that fully exploit the principles of neural computation. Constrained in this way, like the brain, Lava applications allow neuromorphic platforms to intelligently process, learn from, and respond to real-world data with great gains in energy efficiency and speed compared to conventional computer architectures.
In this talk, I will present the main programming model of Lava, enabling the development of custom neuron models. Participants will also learn how to use Lava to train spiking neural networks to solve a classification task on the N-MNIST dataset.
Bio
Bio
Alessandro Pierro is a researcher at the Intel Neuromorphic Computing Lab and a doctoral candidate in computer science at the Ludwig-Maximilians-Universität München. His research aims to develop a methodology for the hardware-aware design of algorithms, with the objective of exploiting parallel architectures for low latency and energy-efficient computing. He is currently focusing on the development of fast combinatorial optimization algorithms on the Intel Loihi 2 neuromorphic research processor.
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