High Performance Graph Mining Systems

Speaker: Xuehai Qian , University of Southern California

Date: Monday, January 11, 2021

Time: 2:00 PM to 3:00 PM Note: all times are in the Eastern Time Zone

Public: Yes

Location: https://mit.zoom.us/meeting/register/tJUrdOqopj8uHdO4gUyVMnfglOFEqIye_Je0 (Registration required, if you haven't registered for this series before)

Event Type: Seminar

Room Description: https://mit.zoom.us/meeting/register/tJUrdOqopj8uHdO4gUyVMnfglOFEqIye_Je0 (Registration required, if you haven't registered for this series before)

Host: Julian Shun, MIT CSAIL

Contact: Julian Shun, jshun@mit.edu, lindalynch@csail.mit.edu

Relevant URL: http://fast-code.csail.mit.edu/

Speaker URL: http://alchem.usc.edu/portal/index.html

Speaker Photo:
None

Reminders to: fast-code-seminar@lists.csail.mit.edu, seminars@csail.mit.edu, pl@csail.mit.edu, commit@lists.csail.mit.edu

Reminder Subject: TALK: High Performance Graph Mining Systems

Abstract: Graph mining, which finds all embeddings matching specific patterns, is a fundamental task in many applications. In this talk, I will present the first graph mining system that decomposes the target pattern into several subpatterns, and then computes the count of each. The system addressed several key challenges including: a partial-embedding-centric programming model supporting advanced graph mining applications; an accurate and efficient cost model based on approximate graph mining; an efficient search method to jointly determine the decomposition of all concrete patterns of an application; and the partial symmetry breaking technique to eliminate redundant enumeration. Our experiments show that the system is significantly faster than all existing state-of-the-art systems and provides a novel and viable path to scale to large patterns. I will also briefly discuss a distributed graph mining system that achieves the high performance with overlapped communication and computation, redundant communication elimination, efficient graph data caching, and NUMA-aware graph data sub-partitioning.

Bio: Xuehai Qian is an assistant professor at University of Southern California. His research interests include domain-specific systems and architectures for emerging applications such as machine learning and graph analytics, and recently hardware security and quantum computing. He got his Ph.D from UIUC. He is the recipient of W.J Poppelbaum Memorial Award at UIUC, NSF CRII and CAREER Award, and the inaugural ACSIC (American Chinese Scholar In Computing) Rising Star Award. He is inducted to the "Hall of Fame" of ASPLOS and HPCA; and Computer Architecture Aggregated Hall-of-Fame. For more details, please visit his research group at: http://alchem.usc.edu/.

IMPORTANT NOTE FOR ATTENDEES: If you have already registered for the Fast Code Seminars on Zoom since July 27, 2020, please use the Zoom link that you have received. This link will stay the same for subsequent Fast Code seminars this semester. Zoom does not recognize a second registration, and will not send out the link a second time. If you have any problems with registration, please contact jshun@mit.edu and lindalynch@csail.mit.edu by 1:30pm on the day of the seminar, so that we can try to resolve it before the seminar begins.

Research Areas:
Programming Languages & Software, Systems & Networking

Impact Areas:
Big Data

See other events that are part of the Fast Code 2020 - 2021.

Created by Julian J. Shun at Saturday, January 02, 2021 at 6:18 PM.