Plenary I
Jason K. Eshraghian, Department of Electrical and Computer Engineering, University of California, Santa Cruz, U.S.A
Large-Scale Neuromorphic Computing on Heterogeneous Systems
In the realm of large-scale model training, the efficiency bottleneck often stems from the intensive data communication required between GPUs. Drawing inspiration from the brain’s remarkable efficiency, this talk explores neuromorphic computing’s potential to mitigate this bottleneck. As chip designers increasingly turn to advanced packaging technologies and chiplets, the models running on these heterogeneous platforms must evolve accordingly. Spiking neural networks, inspired by the brain’s method of encoding information over time and its utilization of fine-grained sparsity for information transfer, are perfectly poised to extract the benefits (and limitations) imposed in heterogeneous hardware systems. This talk will delve into strategies for integrating spiking neural networks into large-scale models and how neuromorphic computing, alongside the utilization of chiplets, can surpass the current capabilities of GPUs, paving the way for the next generation of AI systems.
Biography: Jason K. Eshraghian is an Assistant Professor with the Department of Electrical and Computer Engineering, University of California, Santa Cruz. He received a Bachelor of Engineering (Electrical and Electronic) and a Bachelor of Laws degree from The University of Western Australia, WA, Australia, in 2016, where he also received a Ph.D. Degree in 2019. From 2019 to 2022, he was a Post-Doctoral Research Fellow at the University of Michigan, MI, USA. He serves as the Secretary of the Neural Systems and Applications Technical Committee. He has been awarded four best paper and best live demonstration awards across IEEE journals and conferences. He is the recipient of a Fulbright Fellowship (Australian-American Fulbright Commission), a Forrest Research Fellowship (Forrest Research Foundation), and the Endeavour Research Fellowship (Australian Government). His research interests are in large-scale neuromorphic computing. He is the developer of snnTorch, a widely used Python library with over 100,000 downloads used to train and model spiking neural networks.
Prof. Jason K. Eshraghian is the developer of snnTorch
