*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Umit Catalyurek
Summary Sentence: CSE Faculty Candidate Seminar from Dr. Julian Shun, Miller Research Fellow, University of California - Berkley
Full Summary: No summary paragraph submitted.
Julian Shun, Carnegie Mellon - CSE SeminarAbstract:
Parallelism is the key to achieving high-performance in computing. However, writing efficient and scalable parallel programs is notoriously difficult, and often requires significant expertise. To address this challenge, it is crucial to provide programmers with high-level tools to allow for the development of solutions more easily, and at the same time emphasize the theoretical and practical aspects of algorithm design to allow the developed solutions to run efficiently under many possible settings.My research addresses this challenge using a three-pronged approach via the design of shared-memory programming techniques, frameworks, and algorithms for important problems in computing.
In this talk, Miller Research Fellow Julian Shun will present tools for deterministic parallel programming, large-scale shared-memory algorithms that are efficient both in theory and in practice, and Ligra, a framework for simplifying the programming of shared-memory graph algorithms.
Bio:
Julian Shun is currently a Miller Research Fellow at the University of California, Berkeley (UC Berkeley). He obtained his Ph.D. in Computer Science from Carnegie Mellon University and his undergraduate degree in Computer Science from UC Berkeley. He is interested in developing large-scale parallel algorithms for graph processing, as well as parallel text algorithms and data structures. He is also interested in designing methods for writing deterministic parallel programs and benchmarking parallel programs. He has earned the ACM Doctoral Dissertation Award, CMU School of Computer Science Doctoral Dissertation Award, Miller Research Fellowship, Facebook Graduate Fellowship, and a "Best Student Paper Award" at the Data Compression Conference.
