- Home
- Register
- Attend
- Program
- Technical Program Overview
- SC14 Schedule
- Awards
- Birds-of-a-Feather Sessions (BOFs)
- Emerging Technologies
- Invited Talks
- Panels
- Papers
- Posters
- Scientific Visualization Showcase
- Tutorials
- Workshops
- Doctoral Showcase Program
- HPC Matters Plenary
- Keynote
- SC14 Archive
- SC14 Conference Program
- Tech Program Receptions
- Exhibit
- Engage
- Media
- Media Overview
- Media Releases
- Announcing the Second Test of Time Award Winner
- CDC to Present at Supercomputing 2014
- Finalists Compete for Coveted ACM Gordon Bell Prize in High Performance Computing
- Four Ways Supercomputing Is Changing Lives: From Climate Modeling to Manufacturing Consumer Goods
- Join the Student Cluster Competition
- New Orleans Becomes Home to Fastest Internet Hub in the World
- SC14 Announces New Plenary to Focus on the Importance of Supercomputers in Society
- SC14 Registration Opens, Technical Program Goes Live
- Supercomputing 2014 Recognizes Outstanding Achievements in HPC
- Supercomputing 2014 Sets New Records
- Supercomputing Invited Plenary Talks
- Supercomputing Unveils Ground-Breaking Innovations and the World’s Fastest Computer Network
- World’s Fastest Computer Network Coming to New Orleans
- SC14 Logo Usage
- SC14 Media Partners
- Social Media
- Newsletters
- SC14 Blog
- Opening Press Briefing
- SC Photograph and Film Acceptable Use Policy
- Media Registration
- Video Gallery
- SCinet
SCHEDULE: NOV 16-21, 2014
When viewing the Technical Program schedule, on the far righthand side is a column labeled "PLANNER." Use this planner to build your own schedule. Once you select an event and want to add it to your personal schedule, just click on the calendar icon of your choice (outlook calendar, ical calendar or google calendar) and that event will be stored there. As you select events in this manner, you will have your own schedule to guide you through the week.
Parallel Bayesian Network Structure Learning for Genome-Scale Gene Networks
SESSION: High Performance Genomics
EVENT TYPE: Papers, Best Paper Finalists
TIME: 11:30AM - 12:00PM
SESSION CHAIR: Zhong Jin
AUTHOR(S):Sanchit Misra, Vasimuddin Md, Kiran Pamnany, Sriram P. Chockalingam, Yong Dong, Min Xie, Maneesha R. Aluru, Srinivas Aluru
ROOM:388-89-90
ABSTRACT:
Learning Bayesian networks is NP-hard. Even with recent progress in heuristic and parallel algorithms, modeling capabilities still fall short of the scale of the problems encountered. In this paper, we present a massively parallel method for Bayesian network structure learning, and demonstrate its capability by constructing genome-scale gene networks of the model plant Arabidopsis thaliana from over 168.5 million gene expression values. We report strong scaling efficiency of 75% and demonstrate scaling to 1.57 million cores of the Tianhe-2 supercomputer. Our results constitute three and five orders of magnitude increase over previously published results in the scale of data analyzed and computations performed, respectively. We achieve this through algorithmic innovations, using efficient techniques to distribute work across all compute nodes, all available Intel Xeon processors and Intel Xeon Phi coprocessors on each node, all available threads on each processor and coprocessor, and vectorization techniques to maximize single thread performance.
Chair/Author Details:
Zhong Jin (Chair) - Chinese Academy of Sciences
Sanchit Misra - Intel Corporation
Vasimuddin Md - Indian Institute of Technology Bombay
Kiran Pamnany - Intel Corporation
Sriram P. Chockalingam - Indian Institute of Technology Bombay
Yong Dong - National University of Defense Technology, China
Min Xie - National University of Defense Technology, China
Maneesha R. Aluru - Georgia Institute of Technology
Srinivas Aluru - Georgia Institute of Technology
Click here to download .ics calendar file
Click here to download .vcs calendar file
Click here to add event to your Google Calendar