The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
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
The distributed ASCI Supercomputer project
ACM SIGOPS Operating Systems Review
The ANL/IBM SP Scheduling System
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Towards Convergence in Job Schedulers for Parallel Supercomputers
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Theory and Practice in Parallel Job Scheduling
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
Selective Reservation Strategies for Backfill Job Scheduling
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
Local versus Global Schedulers with Processor Co-allocation in Multicluster Systems
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
The Impact of More Accurate Requested Runtimes on Production Job Scheduling Performance
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
The Performance of Processor Co-Allocation in Multicluster Systems
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Resource Co-Allocation in Computational Grids
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
Characterization of Backfilling Strategies for Parallel Job Scheduling
ICPPW '02 Proceedings of the 2002 International Conference on Parallel Processing Workshops
Recent trends in the marketplace of high performance computing
Parallel Computing
Improving parallel job scheduling performance in multi-clusters through selective job coallocation
Improving parallel job scheduling performance in multi-clusters through selective job coallocation
Parallel job scheduling — a status report
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
Workload characteristics of a multi-cluster supercomputer
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
Are user runtime estimates inherently inaccurate?
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
Pitfalls in parallel job scheduling evaluation
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Using checkpointing to recover from poor multi-site parallel job scheduling decisions
Proceedings of the 5th international workshop on Middleware for grid computing: held at the ACM/IFIP/USENIX 8th International Middleware Conference
Co-allocation with Communication Considerations in Multi-cluster Systems
Euro-Par '08 Proceedings of the 14th international Euro-Par conference on Parallel Processing
PDCS '07 Proceedings of the 19th IASTED International Conference on Parallel and Distributed Computing and Systems
Performance, fairness and effectiveness in space-slicing multi-cluster schedulers
PDCS '07 Proceedings of the 19th IASTED International Conference on Parallel and Distributed Computing and Systems
Resource provisioning in SLA-based cluster computing
JSSPP'10 Proceedings of the 15th international conference on Job scheduling strategies for parallel processing
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Performance evaluation in multi-cluster processor coallocation - like in many other parallel job scheduling problems- is mostly done by computing the average metric value for the entire job stream. This does not give a comprehensive understanding of the relative performance of the different jobs grouped by their characteristics. It is however the characteristics that affect how easy/hard jobs are to schedule. We, therefore, do not get to understand scheduler performance at job type level. In this paper, we study the performance of multi-cluster processor co-allocation for different job groups grouped by their size, components and widest component. We study their relative performance, sensitivity to parameters and how their performance is affected by the heuristics used to break them up into components. We show that the widest component us characteristic that most affects job schedulability. We also show that to get better performance, jobs should be broken up in such a way that the width of the widest component is minimized.