195 citations · 243 across the 6 of their papers we have counts for
3 papers · 1 filter
Netcast: Low-Power Edge Computing with WDM-defined Optical Neural Networks
Ryan Hamerly, Alexander Sludds, Saumil Bandyopadhyay +4
This paper analyzes the performance and energy efficiency of Netcast, a recently proposed optical neural-network architecture designed for edge computing. Netcast performs deep neu…
Delocalized Photonic Deep Learning on the Internet's Edge
Alexander Sludds, Saumil Bandyopadhyay, Zaijun Chen +13
Advances in deep neural networks (DNNs) are transforming science and technology. However, the increasing computational demands of the most powerful DNNs limit deployment on low-pow…
TopoOpt: Co-optimizing Network Topology and Parallelization Strategy for Distributed Training Jobs
Weiyang Wang, Moein Khazraee, Zhizhen Zhong +5
We propose TopoOpt, a novel direct-connect fabric for deep neural network (DNN) training workloads. TopoOpt co-optimizes the distributed training process across three dimensions: c…