Quantifying Scheduling Challenges for Exascale System Software
Abstract
The move towards high-performance computing (HPC) ap- plications comprised of coupled codes and the need to dra- matically reduce data movement is leading to a reexami- nation of time-sharing vs. space-sharing in HPC systems. In this paper, we discuss and begin to quantify the perfor- mance impact of a move away from strict space-sharing of nodes for HPC applications. Specifically, we examine the po- tential performance cost of time-sharing nodes between ap- plication components, we determine whether a simple coor- dinated scheduling mechanism can address these problems, and we research how suitable simple constraint-based opti- mization techniques are for solving scheduling challenges in this regime. Our results demonstrate that current general- purpose HPC system software scheduling and resource al- location systems are subject to significant performance de- ciencies which we quantify for six representative applica- tions. Based on these results, we discuss areas in which ad- ditional research is needed to meet the scheduling challenges of next-generation HPC systems.
- Authors:
-
- University of New Mexico, Albuquerque
- ORNL
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1265620
- DOE Contract Number:
- AC05-00OR22725
- Resource Type:
- Conference
- Resource Relation:
- Conference: ROSS '15 Proceedings of the 5th International Workshop on Runtime and Operating Systems for Supercomputers, Portland, OR, USA, 20150616, 20150616
- Country of Publication:
- United States
- Language:
- English
- Subject:
- D.4.7 [Operating Sytems]: Organization and Design; C.5.1 [Computer System Implementation]: Super (very large) computers; C.1.2 [Multiprocessors]: Parallel Processors
Citation Formats
Mondragon, Oscar, Bridges, Patrick G., and Jones, Terry R. Quantifying Scheduling Challenges for Exascale System Software. United States: N. p., 2015.
Web.
Mondragon, Oscar, Bridges, Patrick G., & Jones, Terry R. Quantifying Scheduling Challenges for Exascale System Software. United States.
Mondragon, Oscar, Bridges, Patrick G., and Jones, Terry R. 2015.
"Quantifying Scheduling Challenges for Exascale System Software". United States.
@article{osti_1265620,
title = {Quantifying Scheduling Challenges for Exascale System Software},
author = {Mondragon, Oscar and Bridges, Patrick G. and Jones, Terry R},
abstractNote = {The move towards high-performance computing (HPC) ap- plications comprised of coupled codes and the need to dra- matically reduce data movement is leading to a reexami- nation of time-sharing vs. space-sharing in HPC systems. In this paper, we discuss and begin to quantify the perfor- mance impact of a move away from strict space-sharing of nodes for HPC applications. Specifically, we examine the po- tential performance cost of time-sharing nodes between ap- plication components, we determine whether a simple coor- dinated scheduling mechanism can address these problems, and we research how suitable simple constraint-based opti- mization techniques are for solving scheduling challenges in this regime. Our results demonstrate that current general- purpose HPC system software scheduling and resource al- location systems are subject to significant performance de- ciencies which we quantify for six representative applica- tions. Based on these results, we discuss areas in which ad- ditional research is needed to meet the scheduling challenges of next-generation HPC systems.},
doi = {},
url = {https://www.osti.gov/biblio/1265620},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jan 01 00:00:00 EST 2015},
month = {Thu Jan 01 00:00:00 EST 2015}
}