An evaluation of parallel job scheduling for ASCI Blue-Pacific
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
IEEE Transactions on Parallel and Distributed Systems
IEEE Software
Evaluation of Job-Scheduling Strategies for Grid Computing
GRID '00 Proceedings of the First IEEE/ACM International Workshop on Grid Computing
On Job Scheduling for HPC-Clusters and the dynP Scheduler
HiPC '01 Proceedings of the 8th International Conference on High Performance Computing
A Gang-Scheduling System for ASCI Blue-Pacific
HPCN Europe '99 Proceedings of the 7th International Conference on High-Performance Computing and Networking
The Self-Tuning dynP Job-Scheduler
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Architecture-Independent Request-Scheduling with Tight Waiting-Time Estimations
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
Improved Utilization and Responsiveness with Gang Scheduling
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
Predicting Application Run Times Using Historical Information
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
An Integrated Approach to Parallel Scheduling Using Gang-Scheduling, Backfilling, and Migration
JSSPP '01 Revised Papers from the 7th International Workshop on Job Scheduling Strategies for Parallel 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
On Advantages of Grid Computing for Parallel Job Scheduling
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
Utilization and Predictability in Scheduling the IBM SP2 with Backfilling
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
Locality of sampling and diversity in parallel system workloads
Proceedings of the 21st annual international conference on Supercomputing
Adaptive middleware supporting scalable performance for high-end network services
Journal of Network and Computer Applications
Enhancements to the decision process of the self-tuning dynp scheduler
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
Reconfigurable gang scheduling algorithm
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
AnthillSched: a scheduling strategy for irregular and iterative I/O-intensive parallel jobs
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Toward balanced and sustainable job scheduling for production supercomputers
Parallel Computing
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The performance of job scheduling policies strongly depends on the properties of the incoming jobs. If the job characteristics often change, the scheduling policy should follow these changes. For this purpose the dynP job scheduler family has been developed. The idea is to dynamically switch the scheduling policy during runtime. In a basic version the policy switching is controlled by two parameters.The basic concept of the self-tuning dynP scheduler is to compute virtual schedules for each policy in every scheduling step. That policy is chosen which generates the 'best' schedule. The performance of the self-tuning dynP scheduler no longer depends on a adequate setting of the input parameters.We use a simulative approach to evaluate the performance of the selftuning dynP scheduler and compare it with previous results. To drive the simulations we use synthetic job sets that are based on trace information from four computing centers (CTC, KTH, PC2, SDSC) with obviously different characteristics.