Dynamic Data Structures on the GPU
Host
Julian Shun
MIT CSAIL
Abstract: Dynamic data structures allow updates to the data structure without having to rebuild it completely. I'll discuss five dynamic GPU data structures that we designed and built - log-structured merge trees, quotient filters, linked lists and hash tables built atop them, dynamic graphs, and B-trees. I'll talk about principles that we followed in building them and what we learned from the experience.
Bio: John Owens is a professor of electrical and computer engineering at the University of California, Davis, where he leads an amazing group of graduate students in a research program centered around parallel computing on the graphics processing unit (GPU). He earned his PhD from Stanford in 2003 and his BS from UC Berkeley in 1995. In January 2020 he bought his kids MIT sweatshirts from the Coop while helping to run the Mystery Hunt; his kids wear them often.
Bio: John Owens is a professor of electrical and computer engineering at the University of California, Davis, where he leads an amazing group of graduate students in a research program centered around parallel computing on the graphics processing unit (GPU). He earned his PhD from Stanford in 2003 and his BS from UC Berkeley in 1995. In January 2020 he bought his kids MIT sweatshirts from the Coop while helping to run the Mystery Hunt; his kids wear them often.