A Parallel Workload Model and its Implications for Maui Scheduling Policies

Author

Liu, Zhuo ; Liang, Aihua ; Xiao, Limin

Author_Institution

Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing, China

Volume

2

fYear

2010

Firstpage

384

Lastpage

389

Abstract

We develop a workload model based on the logs of real workloads of the Linux cluster Atlas and a small IBM blue gene/L cluster at Lawrence Livermore National Laboratory (LLNL), and the 184-node IBM eServer pSeries 655/690 at the San Diego Supercomputer Center (SDSC). This model gives us insight into the performance of scheduling jobs on space-sharing parallel computers, provided by Maui. We find out that backfill queuing policies improve a lot of the system performance, and without reservation, the allocation policies do not have an obvious distance between each other.

Keywords

Linux; pattern clustering; queueing theory; scheduling; IBM blue gene; Lawrence Livermore National Laboratory; Linux cluster Atlas; Maui scheduling policies; San Diego Supercomputer Center; backfill queuing policies; job scheduling; parallel workload model; space-sharing parallel computers; Computational modeling; Computer science; Computer simulation; Concurrent computing; Dynamic programming; Laboratories; Linux; Processor scheduling; Supercomputers; System performance; Maui; evaluation; scheduling policy; workload model;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Modeling and Simulation, 2010. ICCMS '10. Second International Conference on

Conference_Location

Sanya, Hainan

Print_ISBN

978-1-4244-5642-0

Electronic_ISBN

978-1-4244-5643-7

Type

conf

DOI

10.1109/ICCMS.2010.16

Filename

5421118