Name
Abstract | ||
|---|---|---|
This research aims at improving our understanding of backfilling job scheduling algorithms. The most frequently used algorithm, EASY-backfilling, was selected for a performance evaluation by scheduling static workloads of parallel jobs on a computer cluster. To achieve the aim, we have developed a batch job scheduler for Linux clusters, implemented several scheduling algorithms including ARCA and EASY-Backfilling, and carried out their performance evaluation by running well known MPI applications on a real cluster. Our performance evaluation carried out for EASY-Backfilling serves two purposes. First, the performance results obtained from our evaluation can be used to validate other researcherspsila results generated by simulation, and second, the methodology used in our evaluation has alleviated many problems existed in the simulations presented in the current literature. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/CLUSTR.2007.4629218 | Austin, TX |
Keywords | Field | DocType |
Linux,application program interfaces,message passing,performance evaluation,scheduling,workstation clusters,ARCA,EASY-Backfilling,EASY-backfill job scheduling,Linux clusters,MPI,batch job scheduler,computer cluster,performance evaluation | Fair-share scheduling,Computer science,Scheduling (computing),Parallel computing,Real-time computing,Two-level scheduling,Batch processing,Rate-monotonic scheduling,Job scheduler,Dynamic priority scheduling,Computer cluster,Distributed computing | Conference |
ISSN | ISBN | Citations |
1552-5244 E-ISBN : 978-1-4244-1388-1 | 978-1-4244-1388-1 | 12 |
PageRank | References | Authors |
0.71 | 13 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| adam k l wong | 1 | 13 | 1.07 |
| Andrzej M. Goscinski | 2 | 12 | 0.71 |