195 citations · 237 across the 4 of their papers we have counts for
6 papers
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…
Throughput Scaling for MMF-Enabled Optical Datacenter Networks by Time-Slicing-Based Crosstalk Mitigation
Zhizhen Zhong, Nan Hua, Yufang Yu +8
Modal crosstalk is the main bottleneck in MMF-enabled optical datacenter networks with direct detection. A novel time-slicing-based crosstalk-mitigated MDM scheme is first proposed…
Evolving Optical Networks for Latency-Sensitive Smart-Grid Communications via Optical Time Slice Switching (OTSS) Technologies
Zhizhen Zhong, Nan Hua, Zhu Liu +3
In this paper, we proposed a novel OTSS-assisted optical network architecture for smart-grid communication networks, which has unique requirements for low-latency connections. Illu…
On QoS-assured degraded provisioning in service-differentiated multi-layer elastic optical networks
Zhizhen Zhong, Jipu Li, Nan Hua +4
The emergence of new network applications is driving network operators to not only fulfill dynamic bandwidth requirements, but offer various grades of service. Degraded provisionin…