Guided self-scheduling: A practical scheduling scheme for parallel supercomputers
IEEE Transactions on Computers
Performance of the NAS parallel benchmarks on PVM-based networks
Journal of Parallel and Distributed Computing
Using MPI: portable parallel programming with the message-passing interface
Using MPI: portable parallel programming with the message-passing interface
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
Scheduling Parallel Machines On-line
SIAM Journal on Computing
Approximating total flow time on parallel machines
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Scheduling to minimize average completion time: off-line and on-line approximation algorithms
Mathematics of Operations Research
GLUnix: a global layer Unix for a network of workstations
Software—Practice & Experience - Special issue on multiprocessor operating systems
High-throughput resource management
The grid
An evaluation of parallel job scheduling for ASCI Blue-Pacific
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Application-level scheduling on distributed heterogeneous networks
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
Scheduling Algorithms
Ray Tracing Worlds with POV-Ray
Ray Tracing Worlds with POV-Ray
Trapezoid Self-Scheduling: A Practical Scheduling Scheme for Parallel Compilers
IEEE Transactions on Parallel and Distributed Systems
IPPS '99/SPDP '99 Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing
Scheduling Jobs that Arrive Over Time (Extended Abstract)
WADS '95 Proceedings of the 4th International Workshop on Algorithms and Data Structures
Parallel Processing on Dynamic Resources with CARMI
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Using Queue Time Predictions for Processor Allocation
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
Developments from a June 1996 seminar on Online algorithms: the state of the art
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
Conventional Benchmarks as a Sample of the Performance Spectrum
HICSS '98 Proceedings of the Thirty-First Annual Hawaii International Conference on System Sciences-Volume 7 - Volume 7
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
Job Scheduling Strategies for Parallel Processing: 10th International Workshop, JSSPP 2004, New York, NY, USA, June 13, 2004, Revised Selected Papers (Lecture Notes in Computer Science)
A Symbolic Approachto Modeling Cellular Behavior
HiPC '02 Proceedings of the 9th International Conference on High Performance Computing
Selective Reservation Strategies for Backfill Job Scheduling
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
Use of PVFS for Efficient Execution of Jobs with Pipeline-Shared I/O
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
Backfilling with lookahead to optimize the packing of parallel jobs
Journal of Parallel and Distributed Computing
Selective preemption strategies for parallel job scheduling
International Journal of High Performance Computing and Networking
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Networks of workstations offer large amounts of unused processing time. Resource management systems are able to exploit this computing capacity by assigning compute‐intensive tasks to idle workstations. To avoid interferences between multiple, concurrently running applications, such resource management systems have to schedule application jobs carefully. Continuously arriving jobs and dynamically changing amounts of available CPU capacity make traditional scheduling algorithms difficult to apply in workstation networks. Online scheduling algorithms promise better results by adapting schedules to changing situations. This paper compares six online scheduling algorithms by simulating several workload scenarios. Based on the insights gained by simulation, the three online scheduling algorithms performing best were implemented in the Winner resource management system. Experiments conducted with Winner in a real workstation network confirm the simulation results obtained.