9 papers
MARS: Multipath Adaptive Reliable Service
Yitong Li, Xinjiao Li, Dirk Kutscher
Multipath transport is important for Internet/WAN services that move data volumes across heterogeneous paths, including geo-distributed analytics, content distribution, and cloud-s…
MD2G-Cast: Relay-Coordinated Multicast for Scalable Volumetric Streaming over MoQ
Ruonan Chai, Yisu Wang, Zili Meng +1
Volumetric streaming remains difficult to scale because receivers with overlapping fields of view are often served independently, causing repeated transmission of shared content. W…
MultiMoQ: Multi-Access Media-Over-QUIC for Robust Immersive Video Streaming
Yitong Li, Xinjiao Li, Ruonan Chai +1
Live immersive video streaming, particularly 360-degree video, is increasingly adopted in applications such as virtual events, sports broadcasting, and remote education. Existing a…
INDS: Incremental Named Data Streaming for Real-Time Point Cloud Video
Ruonan Chai, Yixiang Zhu, Xinjiao Li +3
Real-time streaming of point cloud video, characterized by massive data volumes and high sensitivity to packet loss, remains a key challenge for immersive applications under dynami…
ViFusion: In-Network Tensor Fusion for Scalable Video Feature Indexing
Yisu Wang, Yixiang Zhu, Xinjiao Li +3
Large-scale video feature indexing in datacenters is critically dependent on efficient data transfer. Although in-network computation has emerged as a compelling strategy for accel…
NetSenseML: Network-Adaptive Compression for Efficient Distributed Machine Learning
Yisu Wang, Xinjiao Li, Ruilong Wu +2
Training large-scale distributed machine learning models imposes considerable demands on network infrastructure, often resulting in sudden traffic spikes that lead to congestion, i…
Rethinking Dynamic Networks and Heterogeneous Computing with Automatic Parallelization
Ruilong Wu, Xinjiao Li, Yisu Wang +2
Hybrid parallelism techniques are essential for efficiently training large language models (LLMs). Nevertheless, current automatic parallel planning frameworks often overlook the s…
PacTrain: Pruning and Adaptive Sparse Gradient Compression for Efficient Collective Communication in Distributed Deep Learning
Yisu Wang, Ruilong Wu, Xinjiao Li +1
Large-scale deep neural networks (DNN) exhibit excellent performance for various tasks. As DNNs and datasets grow, distributed training becomes extremely time-consuming and demands…
Affordable HPC: Leveraging Small Clusters for Big Data and Graph Computing
Ruilong Wu, Yisu Wang, Dirk Kutscher
This study explores strategies for academic researchers to optimize computational resources within limited budgets, focusing on building small, efficient computing clusters. It del…