Adaptive load sharing in homogeneous distributed systems
IEEE Transactions on Software Engineering
The grid
Gallop: the benefits of wide-area computing for parallel processing
Journal of Parallel and Distributed Computing
Job scheduling in the presence of multiple resource requirements
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Design and implementations of Ninf: towards a global computing infrastructure
Future Generation Computer Systems - Special issue on metacomputing
Benchmarking and comparison of the task graph scheduling algorithms
Journal of Parallel and Distributed Computing
Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
Enabling Technologies for Computational Science: Frameworks, Middleware and Environments
Enabling Technologies for Computational Science: Frameworks, Middleware and Environments
Predicting the cost and benefit of adapting data parallel applications in clusters
Journal of Parallel and Distributed Computing
CASCH: A Tool for Computer-Aided Scheduling
IEEE Concurrency
Adaptive Parallelism and Piranha
Computer
PUNCH: Web Portal for Running Tools
IEEE Micro
A taxonomy of scheduling in general-purpose distributed computing systems
IEEE Transactions on Software Engineering
Maximizing Speedup through Self-Tuning of Processor Allocation
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
A Model for Moldable Supercomputer Jobs
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Job Characteristics of a Production Parallel Scientivic Workload on the NASA Ames iPSC/860
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Parallel Job Scheduling: Issues and Approaches
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Workload Evolution on the Cornell Theory Center IBM SP2
IPPS '96 Proceedings of the Workshop on 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
Gang scheduling for highly efficient, distributed multiprocessor systems
FRONTIERS '96 Proceedings of the 6th Symposium on the Frontiers of Massively Parallel Computation
Scheduling From the Perspective of the Application
HPDC '96 Proceedings of the 5th IEEE International Symposium on High Performance Distributed Computing
Prediction and Adaptation in Active Harmony
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
Toward a Common Component Architecture for High-Performance Scientific Computing
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
Improving Parallel Job Scheduling by Combining Gang Scheduling and Backfilling Techniques
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
MULTITHREADED MODEL FOR DYNAMIC LOAD BALANCING PARALLEL ADAPTIVE PDE COMPUTATIONS
MULTITHREADED MODEL FOR DYNAMIC LOAD BALANCING PARALLEL ADAPTIVE PDE COMPUTATIONS
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
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 10 - Volume 11
Performance-Driven Processor Allocation
IEEE Transactions on Parallel and Distributed Systems
Future Generation Computer Systems
Competitive online adaptive scheduling for sets of parallel jobs with fairness and efficiency
Journal of Parallel and Distributed Computing
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This paper presents a new paradigm for parallel job scheduling called integrated scheduling or iScheduling. The iScheduler is an application-aware job scheduler as opposed to a general-purpose system scheduler. It dynamically controls resource allocation among a set of competing applications, but unlike a traditional job scheduler, it can interact directly with an application during execution to optimize resource allocation. An iScheduler may add or remove resources from a running application to improve the performance of other applications. Such fluid resource management can support both improved application and system performance. We propose a framework for building iSchedulers and evaluate the concept on several workload traces obtained both from supercomputer centers and from a set of real parallel jobs. The results indicate that iScheduling can improve both waiting time and overall turnaround time substantially for these workload classes, outperforming standard policies such as backfilling and moldable job scheduling.