Job Scheduling Strategies for Parallel Processing: IPPS '96 Workshop, Honolulu, Hawaii, April 16, 1996. Proceedings
Springer Science & Business Media, 1996. gada 16. okt. - 289 lappuses
This book constitutes the strictly refereed post-workshop proceedings of the International Workshop on Job Scheduling Strategies for Parallel Processing, held in conjunction with IPPS '96 symposium in Honolulu, Hawaii, in April 1996.
The book presents 15 thoroughly revised full papers accepted for inclusion on the basis of the reports of at least five program committee members. The volume is a highly competent contribution to advancing the state-of-the-art in the area of job scheduling for parallel supercomputers. Among the topics addressed are job scheduler, workload evolution, gang scheduling, multiprocessor scheduling, parallel processor allocation, and distributed memory environments.
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Toward Convergence in Job Schedulers for Parallel Supercomputers
Workload Evolution on the Cornell Theory Center IBM SP2
The EASY LoadLeveler API Project
A Batch Scheduler for the Intel Paragon with a Noncontiguous Node Allocation Algorithm
ArchitectureIndependent RequestScheduling with Tight WaitingTime Estimations
Packing Schemes for Gang Scheduling
A Gang Scheduling Design for Multiprogrammed Parallel Computing Environments
Implementation of GangScheduling on Workstation Cluster
Using Runtime Measured Workload Characteristics in Parallel Processor Scheduling
Parallel Application Characterization for Multiprocessor Scheduling Policy Design
Dynamic vs Static QuantumBased Parallel Processor Allocation
An Empirical Comparison
Dynamic Partitioning in Different DistributedMemory Environments
LocalityInformationBased Scheduling in SharedMemory Multiprocessors
Managing Checkpoints for Parallel Programs
algorithm allocation applications approach architecture Arrival Rate assume average batch block cache called changes characteristics checkpoint communication compared Computer considered context cost curves depends developed distributed dynamic dynamic partitioning EASY efficiency environment estimations Evaluation example execution Feitelson Figure Folding function gang scheduling given idle implemented important improve increase interactive Interval Job Scheduling limit load LoadLeveler machine maximum mean measurements memory multiprocessor nodes Notes number of processors operating overhead Parallel Processing partition performance periods possible preemption present problem Proceedings quantum queue reduce relative repartitioning representative request requirements response runtime scheduling policies Scheduling Strategies scheme Science seconds server sharing shows single slots specific speedup switch Table thread utilization wait workload workstation