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Title: Quantifying Scheduling Challenges for Exascale System Software

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.
 [1] ;  [1] ;  [2]
  1. University of New Mexico, Albuquerque
  2. ORNL
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Conference: ROSS '15 Proceedings of the 5th International Workshop on Runtime and Operating Systems for Supercomputers, Portland, OR, USA, 20150616, 20150616
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)
Country of Publication:
United States
D.4.7 [Operating Sytems]: Organization and Design; C.5.1 [Computer System Implementation]: Super (very large) computers; C.1.2 [Multiprocessors]: Parallel Processors