Allocating Independent Subtasks on Parallel Processors
IEEE Transactions on Software Engineering
Guided self-scheduling: A practical scheduling scheme for parallel supercomputers
IEEE Transactions on Computers
Algorithmic skeletons: structured management of parallel computation
Algorithmic skeletons: structured management of parallel computation
Safe self-scheduling: a parallel loop scheduling scheme for shared-memory multiprocessors
International Journal of Parallel Programming
Allocating independent tasks to parallel processors: an experimental study
Journal of Parallel and Distributed Computing - Special issue on dynamic load balancing
Divisible task scheduling — concept and verification
Parallel Computing - Special issue on task scheduling problems for parallel and distributed systems
Future Generation Computer Systems - Special issue on metacomputing
A Novel Data Distribution Technique for Host-Client Type Parallel Applications
IEEE Transactions on Parallel and Distributed Systems
Scheduling Divisible Loads in Parallel and Distributed Systems
Scheduling Divisible Loads in Parallel and Distributed Systems
Scheduling divisible workloads on heterogeneous platforms
Parallel Computing - Parallel matrix algorithms and applications (PMAA '02)
Scheduling Strategies for Master-Slave Tasking on Heterogeneous Processor Platforms
IEEE Transactions on Parallel and Distributed Systems
Scheduling Divisible Loads on Star and Tree Networks: Results and Open Problems
IEEE Transactions on Parallel and Distributed Systems
Practical Divisible Load Scheduling on Grid Platforms with APST-DV
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
A Grid-Based Stochastic Simulation of Unitary and Membrane Ca^2+ Currents in Spherical Cells
CBMS '05 Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems
IEEE Transactions on Parallel and Distributed Systems
Multiround Algorithms for Scheduling Divisible Loads
IEEE Transactions on Parallel and Distributed Systems
Self-adaptive skeletal task farm for computational grids
Parallel Computing - Algorithmic skeletons
Multi-installment divisible load processing in heterogeneous distributed systems: Research Articles
Concurrency and Computation: Practice & Experience - Parallel and Distributed Computing (EuroPar 2005)
Resource-Aware Distributed Scheduling Strategies for Large-Scale Computational Cluster/Grid Systems
IEEE Transactions on Parallel and Distributed Systems
Dynamic load balancing with adaptive factoring methods in scientific applications
The Journal of Supercomputing
Minimizing the stretch when scheduling flows of divisible requests
Journal of Scheduling
Scheduling multiple divisible loads in homogeneous star systems
Journal of Scheduling
An adaptive skeletal task farm for grids
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Design and implementation of parallel video encoding strategies using divisible load analysis
IEEE Transactions on Circuits and Systems for Video Technology
A survey of algorithmic skeleton frameworks: high-level structured parallel programming enablers
Software—Practice & Experience - Focus on Selected PhD Literature Reviews in the Practical Aspects of Software Technology
Performance evaluation of MapReduce using full virtualisation on a departmental cloud
International Journal of Applied Mathematics and Computer Science - SPECIAL SECTION: Efficient Resource Management for Grid-Enabled Applications
Cluster-based optimized parallel video transcoding
Parallel Computing
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This article presents a statistical approach to the scheduling of divisible workloads. Structured as a task farm with different scheduling modes including adaptive single and multi-round scheduling, this novel divisible load theory approach comprises two phases, calibration and execution, which dynamically adapt the installment size and number. It introduces the concept of a generic installment factor based on the statistical dispersion of the calibration times of the participating nodes, which allows automatic determination of the number and size of the workload installments. Initially, the calibration ranks processors according to their fitness and determines an installment factor based on how different their execution times are. Subsequently, the execution iteratively distributes the workload according to the processor fitness, which is continuously re-assessed throughout the program execution. Programmed as an adaptive algorithmic skeleton, our task farm has been successfully evaluated for single-round scheduling and generic multi-round scheduling using a computational biology parameter-sweep in a non-dedicated multi-cluster system.