Bin packing with divisible item sizes
Journal of Complexity
An evaluation of parallel job scheduling for ASCI Blue-Pacific
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Impact of job mix on optimizations for space sharing schedulers
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
Job Scheduling in a Partitionable Mesh Using a Two-Dimensional Buddy System Partitioning Scheme
IEEE Transactions on Parallel and Distributed Systems
Job Scheduling is More Important than Processor Allocation for Hypercube Computers
IEEE Transactions on Parallel and Distributed Systems
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
Towards Convergence in Job Schedulers for Parallel Supercomputers
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
A Historical Application Profiler for Use by Parallel Schedulers
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Job Scheduling Scheme for Pure Space Sharing Among Rigid Jobs
IPPS/SPDP '98 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
Production Job Scheduling for Parallel Shared Memory Systems
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Selective Reservation Strategies for Backfill Job Scheduling
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
Parallel computer workload modeling with markov chains
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
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A workload characteristic on a parallel computer depends on an administration policy or a user community for the computer system. An administrator of a parallel computer system needs to select an appropriate scheduling algorithm that schedules multiple jobs on the computer system efficiently. The goal of the work presented in this paper is to investigate mechanisms how job size characteristics affect job scheduling performance. For this goal, this paper evaluates the performance of job scheduling algorithms under various workload models, each of which has a certain characteristic related to the number of processors requested by a job, and analyzes the mechanism for job size characteristics that affect job scheduling performance significantly in the evaluation. The results showed that: (1) most scheduling algorithms classified into the first-fit scheduling showed best performance and were not affected by job size characteristics, (2) certain job size characteristics affected performance of priority scheduling significantly. The analysis of the results showed that the LJF algorithm, which dispatched the largest job first, would perfectly pack jobs to idle processors at high load, where all jobs requested power-of-two processors and the number of processors on a parallel computer was power-of-two.