Evaluation of design choices for gang scheduling using distributed hierarchical control
Journal of Parallel and Distributed Computing
An evaluation of parallel job scheduling for ASCI Blue-Pacific
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Reconfigurable computing: a survey of systems and software
ACM Computing Surveys (CSUR)
IEEE Software
Gang Scheduling with a Queue for Large Jobs
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Packing Schemes for Gang Scheduling
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
Metrics and Benchmarking for Parallel Job Scheduling
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Benchmarks and Standards for the Evaluation of Parallel Job Schedulers
IPPS/SPDP '99/JSSPP '99 Proceedings of the Job Scheduling Strategies for Parallel Processing
A Self-Tuning Job Scheduler Family with Dynamic Policy Switching
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
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
IEEE Transactions on Parallel and Distributed Systems
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Using a single traditional gang scheduling algorithm cannot provide the best performance for all workloads and parallel architectures. A solution for this problem is an algorithm that is capable of dynamically changing its form (configuration) into a more appropriate one, according to environment variations and user requirements. In this paper, we propose, implement and analyze the performance of a Reconfigurable Gang Scheduling Algorithm (RGSA) using simulation. A RGSA uses combinations of independent features that are often implemented in GSAs such as: packing and re-packing schemes (alternative scheduling etc.), multiprogramming levels etc. Ideally, the algorithm may assume infinite configurations and it reconfigures itself according to entry parameters such as: performance metrics (mean utilization, mean response time of jobs etc.) and workload characteristics (mean execution time of jobs, mean parallelism degree of jobs etc.). Also ideally, a reconfiguration causes the algorithm to output the best configuration for a particular situation considering the system's state at a given moment. The main contributions of this paper are: the definition, proposal, implementation and performance analysis of RGSA.