.png){kind=icon}
Return
Data-Aware Task Dispatching for Batch Queuing System
.png){kind=icon}
PRE
AI
DOI：10.1109/JSYST.2015.2471850.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper describes a scheduling method focusing on exploiting the local access of a nonuniform storage-access file system. In our approach, the file access cost is calculated and combined with the CPU load average into a comprehensive value, which will be used as the standard for scheduling. We evaluated our approach in comparison with the original Torque scheduler using three benchmarks: thput-gfpio, readgf, and BLAST benchmarks. For thput- gfpio, the read throughput showed a 3.59 times boost, whereas for readgf, the total execution time was reduced to about 1/10th of the original value. Finally, using the BLAST benchmark, the total execution time was reduced by 33%.
Keywords:
Batch queuing system
data-aware task scheduling
file locality
Gfarm
nonuniform storage-access (NUSA)
scheduling
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
I
IF:
2.4
Papers:
4.5K
Citations:
387
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveShareSave
ShareSave
View more