The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
The Effect of Real Workloads and Synthetic Workloads on the Performance of Job Scheduling for Non-Contiguous Allocation in 2D Mesh Multicomputers
Abstract
The performance of non-contiguous allocation has been traditionally carried out by means of simulations based on synthetic workloads, and also it can be significantly affected by the job scheduling strategy used for determining the order in which jobs are selected for execution. To validate the performance of the non-contiguous allocation algorithms, there has been a need to evaluate the algorithm's performance based on a real workload trace. In this paper, the performance of the well-known Greedy Available Busy List (GABL) non-contiguous allocation strategy for 2D mesh-connected multicomputers is revisited considering several important job scheduling strategies based on a real workload trace, and the results are compared to those obtained from using a synthetic workload. The scheduling strategies used are the First-Come-First-Served (FCFS), Out-of-Order (OO), and Window-Based job scheduling strategies. These strategies have been selected because they are common and they have been used in related works (Ababneh & Bani-Mohammad, 2011). Extensive simulation results based on synthetic and real workload models indicate that the Window-Based job scheduling strategy can improve both overall system performance and fairness (i.e., maximum job waiting delays) by adopting a large job scheduling window. Moreover, the relative performance merits of the scheduling strategies when a real workload trace is used are in general compatible with those obtained when a synthetic workload is used.
Related Content
Honglong Xu, Zhonghao Liang, Kaide Huang, Guoshun Huang, Yan He.
© 2024.
17 pages.
|
Sherin Eliyas, P. Ranjana.
© 2024.
10 pages.
|
Shuang Li, Xiaoguo Yao.
© 2024.
16 pages.
|
Jialan Sun.
© 2024.
21 pages.
|
Mei Gong, Bingli Mo.
© 2024.
15 pages.
|
Qian He, Ke Wang.
© 2024.
19 pages.
|
Sunil Kumar, Rashmi Mishra, Tanvi Jain, Achyut Shankar.
© 2024.
12 pages.
|
|
|