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Title: 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:
 [1];  [1];  [2]
  1. University of New Mexico, Albuquerque
  2. 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}
}

Conference:
Other availability
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