Gang Scheduling with a Queue for Large Jobs
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
The ANL/IBM SP Scheduling System
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Packing Schemes for Gang Scheduling
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
The EASY - LoadLeveler API Project
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Job Re-pacing for Enhancing the Performance of Gang Scheduling
IPPS/SPDP '99/JSSPP '99 Proceedings of the Job Scheduling Strategies for Parallel Processing
Resource Allocation Schemes for Gang Scheduling
IPDPS '00/JSSPP '00 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
A parallel workload model and its implications for processor allocation
HPDC '97 Proceedings of the 6th IEEE International Symposium on High Performance Distributed Computing
Gang Scheduling with Memory Considerations
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
Improving Parallel Job Scheduling by Combining Gang Scheduling and Backfilling Techniques
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
Benefit of Limited Time Sharing in the Presence of Very Large Parallel Jobs
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
| Hi-index | 0.00 |
Applying gang scheduling can alleviate the blockade problem caused by exclusively space-sharing scheduling. To simply allow jobs to run simultaneously on the same processors as in the conventional gang scheduling, however, may introduce a large number of time slots in the system. In consequence the cost of context switches will be greatly increased, and each running job can only obtain a small portion of resources including memory space and processor utilisation and so no jobs can finish their computations quickly. In this paper we present some experimental results to show that to properly divide jobs into different classes and to apply different scheduling strategies to jobs of different classes can greatly reduce the average number of time slots in the system and significantly improve the performance in terms of average slowdown.