QBETS: Queue Bounds Estimation from Time Series Daniel Nurmi University of California Santa Barbara John Brevik California State University, Long Beach Rich Wolski University of California Santa Barbara nurmi@cs.ucsb.edu jbrevik@csulb.edu rich@cs.ucsb.edu Categories and Subject Descriptors G.3 [Probability and Statistics]: Nonparametric statistics x 10 1.5 General Terms Measurement, Experimentation, Performance Keywords super-computing, queue prediction, batch scheduling 0.5 1. INTRODUCTION 0 1.11 1.115 1.12 1.125 1.13 x 10 Typically, high performance compute (HPC) resources are managed using space sharing, a scheduling strategy in which each program is allocated a dedicated set of processors for the duration of its execution. Because each program in a space-shared environment runs in its own dedicated partition of the target machine, a program cannot be initiated until there are a su cient number of processors available for it to use. When a program must wait before it can be initiated, it is queued as a job along with a description of any parameters and environmental inputs (e.g. input les, shell environment variables, etc.) it will require to run. However, because of the need both to assign di erent priorities to users and to improve the overall e ciency of the resource, most installations
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QBETS: queue bounds estimation from time series
Nurmi, Daniel Charles; Brevik, John; Wolski, Rich
Follow ACM SIGMETRICS Performance Evaluation Review
, Volume 35 (1)
Association for Computing Machinery – Jun 12, 2007
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