4 citations · 4 across the 6 of their papers we have counts for
7 papers
UCCL-Zip: Lossless Compression Supercharged GPU Communication
Shuang Ma, Chon Lam Lao, Zhiying Xu +8
The rapid growth of large language models (LLMs) has made GPU communication a critical bottleneck. While prior work reduces communication volume via quantization or lossy compressi…
MXDAG: A Hybrid Abstraction for Cluster Applications
Weitao Wang, Sushovan Das, Xinyu Crystal Wu +3
Distributed applications, such as database queries and distributed training, consist of both compute and network tasks. DAG-based abstraction primarily targets compute tasks and ha…
Efficient and Less Centralized Federated Learning
Li Chou, Zichang Liu, Zhuang Wang +1
With the rapid growth in mobile computing, massive amounts of data and computing resources are now located at the edge. To this end, Federated learning (FL) is becoming a widely ad…
Shufflecast: An Optical, Data-rate Agnostic and Low-Power Multicast Architecture for Next-Generation Compute Clusters
Sushovan Das, Afsaneh Rahbar, Xinyu Crystal Wu +4
An optical circuit-switched network core has the potential to overcome the inherent challenges of a conventional electrical packet-switched core of today's compute clusters. As opt…
MergeComp: A Compression Scheduler for Scalable Communication-Efficient Distributed Training
Zhuang Wang, Xinyu Wu, T. S. Eugene Ng
Large-scale distributed training is increasingly becoming communication bound. Many gradient compression algorithms have been proposed to reduce the communication overhead and impr…
Delay-Energy Joint Optimization for Task Offloading in Mobile Edge Computing
Zhuang Wang, Weifa Liang, Meitian Huang +1
Mobile-edge computing (MEC) has been envisioned as a promising paradigm to meet ever-increasing resource demands of mobile users, prolong battery lives of mobile devices, and short…