Prof. Yinghui Wu, a former postdoc in Prof. Xifeng Yan's lab, receives the 2017 SIGMOD Best Paper Award. Prof. Wu spent three years as a postdoctoral research scientist during Aug 2011 - Aug 2014 at UCSB's CS Department, and then went on to become a professor in the School of EECS at Washington State University.

In this work titled "Parallelizing Sequential Graph Computations", the research team presents GRAPE, a parallel system for graph computations. GRAPE differs from prior systems in its ability to parallelize existing sequential graph algorithms as a whole. Underlying GRAPE are a simple programming model and a principled approach, based on partial evaluation and incremental computation. We show that sequential graph algorithms can be "plugged into" GRAPE with minor changes, and get parallelized. As long as the sequential algorithms are correct, their GRAPE parallelization guarantees to terminate with correct answers under a monotonic condition. Moreover, we show that algorithms in MapReduce, BSP and PRAM can be optimally simulated on GRAPE. In addition to the ease of programming, we experimentally verify that GRAPE achieves comparable performance to the state-of-the-art graph systems, using real-life and synthetic graphs.

SIGMOD, the ACM Special Interest Group on Management of Data is concerned with the principles, techniques and applications of database management systems and data management technology. SIGMOD sponsors the annual SIGMOD/PODS conference, one of the most important and selective in the field of databases.