Moe Kayali
I'm a PhD student in the database group at the University of Washington, Seattle. I work on discovering new techniques to accelerate data management and make its results more trustworthy.
Session
07-27
10:30
30min
Analyzing Large Graphs with QuasiStableColors.jl
Moe Kayali
Graphs (aka networks) are a key part of the data science pipeline at many organizations. However, scalability is the most frequently reported limitation by graph analysts. I introduce QuasiStableColors.jl, a Julia library for approximate graph analysis. On tasks such as ranking node importance (centrality) it enables an over 10x speedup while introducing less than 5% error. In this talk, I will demonstrate how to use this novel graph compression for your own workloads.
JuliaCon
32-123