10 citations · 14 across the 6 of their papers we have counts for
4 papers · 1 filter
ThunderRW: An In-Memory Graph Random Walk Engine (Complete Version)
Shixuan Sun, Yuhang Chen, Shengliang Lu +2
As random walk is a powerful tool in many graph processing, mining and learning applications, this paper proposes an efficient in-memory random walk engine named ThunderRW. Compare…
Cache-Efficient Fork-Processing Patterns on Large Graphs
Shengliang Lu, Shixuan Sun, Johns Paul +2
As large graph processing emerges, we observe a costly fork-processing pattern (FPP) that is common in many graph algorithms. The unique feature of the FPP is that it launches many…
Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload
Johan Kok Zhi Kang, Gaurav, Sien Yi Tan +3
The use of deep learning models for forecasting the resource consumption patterns of SQL queries have recently been a popular area of study. With many companies using cloud platfor…
PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration
Shixuan Sun, Yuhang Chen, Bingsheng He +1
We study the hop-constrained s-t path enumeration (HcPE) problem, which takes a graph , two distinct vertices and a hop constraint as input, and outputs all paths from…