SCS Seminar: Xuehai Qian

Event Details
  • Date/Time:
    • Thursday May 3, 2018 - Friday May 4, 2018
      11:00 am - 11:59 am
  • Location: KACB 1116W
  • Phone:
  • URL:
  • Email:
  • Fee(s):
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Tess Malone, Communications Officer


Summary Sentence: Efficient Graph Processing with Cross-Stack Optimization

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  • Xuehai Qian Xuehai Qian

TITLE: Efficient Graph Processing with Cross-Stack Optimization


Graph analytics has emerged as an important way to understand the relationships between the heterogeneous types of data, allowing data analysts to draw valuable insights. However, graph processing poses key challenges for both architecture and runtime system. In this talk, I will demonstrate efficient graph processing at different scales with cross-stack optimization. First, I will present a distributed graph processing system using 3D graph partition to reduce communication. Next, I will present a out-of-core graph processing system using graph abstraction to accelerate convergence. Finally, I will discuss a graph processing accelerator based on the emerging ReRAM technology.



Xuehai Qian is an assistant professor at the Ming Hsieh Department of Electrical Engineering and the Department of Computer Science at the University of Southern California. He received the Ph.D. from the Computer Science Department at University of Illinois at Urbana-Champaign working on parallel computer architecture. Prior to joining USC, he was a postdoctoral researcher at UC Berkeley. His recent research interests include system and architecture for graph processing, machine learning acceleration, NVM, and cloud system. He is the recipient of NSF CRII award and CAREER award.

Additional Information

In Campus Calendar

College of Computing, School of Computer Science

Invited Audience
Faculty/Staff, Postdoc, Public, Graduate students, Undergraduate students
Seminar/Lecture/Colloquium, Student sponsored
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  • Created By: Tess Malone
  • Workflow Status: Published
  • Created On: Apr 27, 2018 - 3:26pm
  • Last Updated: Apr 27, 2018 - 3:28pm