Name
Abstract | ||
|---|---|---|
To more effectively use a network of high performance computing clusters, allocating multi-process jobs across multiple connected clusters becomes an attractive possibility. This allocation process entails dividing the processes of a job among several clusters, which we refer to as co-allocation. Co-allocation offers the possibility of more efficient use of computer resources, reduced turn-around time and computations using numbers of processes larger than processes on any single cluster. In order to realize these possibilities, effective co-allocation, ultimately, depends on the inter-cluster communication cost. In this paper, we introduce a scalable co-allocation strategy called the Maximum Bandwidth Adjacent cluster Set (MBAS) strategy. The strategy makes use of two thresholds to control allocation: one to control the limit on bandwidth on usable inter-cluster communication links and another to control how jobs are split. A simulator that can simulate the dynamic behavior of jobs running across multiple clusters was developed and used to examine the performance of the MBAS co-allocation strategy. Our results indicate that by adjusting the thresholds for link level control and chunk size control in splitting jobs, the MBAS co-allocation strategy can significantly improve both user satisfaction and system utilization. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s10586-009-0087-x | Cluster Computing |
Keywords | Field | DocType |
Resource management,Job co-allocation,Job scheduling,HPC clusters,Performance evaluation | USable,Resource management,Cluster (physics),Computer science,Link level,Real-time computing,Bandwidth (signal processing),Job scheduler,Computation,Distributed computing,Scalability | Journal |
Volume | Issue | ISSN |
12 | 3 | 1386-7857 |
Citations | PageRank | References |
2 | 0.39 | 18 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinhui Qin | 1 | 14 | 3.82 |
| Michael A. Bauer | 2 | 331 | 78.68 |