- Home
- Register
- Attend
- Conference Program
- SC15 Schedule
- Technical Program
- Awards
- Students@SC
- Research with SCinet
- HPC Impact Showcase
- HPC Matters Plenary
- Keynote Address
- Support SC
- SC15 Archive
- Exhibits
- Media
- SCinet
- HPC Matters
SCHEDULE: NOV 15-20, 2015
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.
Improving Backfilling by using Machine Learning to Predict Running Times
SESSION: Resource Management
EVENT TYPE: Papers
EVENT TAG(S): System Software, Resource Management
TIME: 10:30AM - 11:00AM
SESSION CHAIR(S): Kim Cupps
AUTHOR(S):Eric Gaussier, David Glesser, Valentin Reis, Denis Trystram
ROOM:19AB
ABSTRACT:
The job management system is the HPC middleware responsible for distributing computing power to applications. While such systems generate an ever increasing amount of data, they are characterized by uncertainties on some parameters like the job running times. The question raised in this work is: To what extent is it possible/useful to take into account predictions on the job running times for improving the global scheduling?
We present a comprehensive study for answering this question assuming the popular EASY backfilling policy. More precisely, we rely on some classical methods in machine learning and propose new cost functions well-adapted to the problem. Then, we assess our proposed solutions through intensive simulations using several production logs. Finally, we propose a new scheduling algorithm that outperforms the
popular EASY backfilling algorithm by 28% considering the average bounded slowdown objective.
Chair/Author Details:
Kim Cupps (Chair) - Lawrence Livermore National Laboratory|
Eric Gaussier - University Grenoble Alpes
David Glesser - BULL
Valentin Reis - University Grenoble Alpes
Denis Trystram - University Grenoble Alpes
Click here to download .ics calendar file
Click here to download .vcs calendar file
Click here to add event to your Google Calendar