Designing Parallel Algorithms

Speaker:       Yan Gu

Time:            9:30 am, Sep. 19th.

Location:      SIST 1A200

Host:             Prof. Haoxian Chen

Abstract:

With the advent of modern hardware, parallelism has been more important than ever, and top-tier conference papers reporting performance results are rarely run sequentially. Parallel algorithms have been extensively studied since the 1970s, so what's new and still needs to be explored?  In this talk, I argue that there are still numerous important directions to investigate. I will briefly overview some of my recent work on graph analytics (SSSP, connectivity, k-core, etc.), data structure design (search trees, priority queues, kd-trees, etc.), and highlight ongoing challenges such as space-efficiency, synchronization costs, and the need for simplicity.

Bio:

Yan Gu is an Associate Professor in the Computer Science and Engineering (CSE) Department at UC Riverside. He completed his PhD at Carnegie Mellon University in 2018 and his Bachelor’s degree at Tsinghua University in 2012. Before joining UCR, he spent one year as a postdoc at MIT. His research interest lies in designing simple and efficient algorithms with strong theoretical guarantees and good practical performance. He is a recipient of the NSF CAREER Award and the Google Research Scholar Program in 2024. He has Best Papers and Best Paper Finalists at ICS'25, SPAA'24, PPoPP'23, ESA'23, VLDB'23, and SPAA'20.