62 citations · 537 across the 44 of their papers we have counts for
8 papers · 1 filter
TensorOpt: Exploring the Tradeoffs in Distributed DNN Training with Auto-Parallelism
Zhenkun Cai, Kaihao Ma, Xiao Yan +5
A good parallelization strategy can significantly improve the efficiency or reduce the cost for the distributed training of deep neural networks (DNNs). Recently, several methods h…
Pyramid: A General Framework for Distributed Similarity Search
Shiyuan Deng, Xiao Yan, Kelvin K. W. Ng +2
Similarity search is a core component in various applications such as image matching, product recommendation and low-shot classification. However, single machine solutions are usua…
Scalable De Novo Genome Assembly Using Pregel
Da Yan, Hongzhi Chen, James Cheng +2
De novo genome assembly is the process of stitching short DNA sequences to generate longer DNA sequences, without using any reference sequence for alignment. It enables high-throug…
G-thinker: Big Graph Mining Made Easier and Faster
Da Yan, Hongzhi Chen, James Cheng +3
This paper proposes a general system for compute-intensive graph mining tasks that find from a big graph all subgraphs that satisfy certain requirements (e.g., graph matching and c…
Quegel: A General-Purpose Query-Centric Framework for Querying Big Graphs
Da Yan, James Cheng, M. Tamer Özsu +5
Pioneered by Google's Pregel, many distributed systems have been developed for large-scale graph analytics. These systems expose the user-friendly "think like a vertex" programming…
Lightweight Fault Tolerance in Large-Scale Distributed Graph Processing
Da Yan, James Cheng, Fan Yang
The success of Google's Pregel framework in distributed graph processing has inspired a surging interest in developing Pregel-like platforms featuring a user-friendly "think like a…
Efficient Processing of Very Large Graphs in a Small Cluster
Da Yan, Yuzhen Huang, James Cheng +1
Inspired by the success of Google's Pregel, many systems have been developed recently for iterative computation over big graphs. These systems provide a user-friendly vertex-centri…
Effective Techniques for Message Reduction and Load Balancing in Distributed Graph Computation
Da Yan, James Cheng, Yi Lu +1
Massive graphs, such as online social networks and communication networks, have become common today. To efficiently analyze such large graphs, many distributed graph computing syst…