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
Communications of the ACM
Factoring: a method for scheduling parallel loops
Communications of the ACM
Trapezoid Self-Scheduling: A Practical Scheduling Scheme for Parallel Compilers
IEEE Transactions on Parallel and Distributed Systems
A Class of Loop Self-Scheduling for Heterogeneous Clusters
CLUSTER '01 Proceedings of the 3rd IEEE International Conference on Cluster Computing
Overhead Analysis of a Dynamic Load Balancing Library for Cluster Computing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 1 - Volume 02
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
An Enhanced Parallel Loop Self-Scheduling Scheme for Cluster Environments
The Journal of Supercomputing
Distributed loop-scheduling schemes for heterogeneous computer systems: Research Articles
Concurrency and Computation: Practice & Experience
A Convergence Study of the Discrete FGDLS Algorithm
IEICE - Transactions on Information and Systems
Loosely-coupled loop scheduling in computational grids
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
A performance-based parallel loop self-scheduling on grid computing environments
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
A hybrid parallel loop scheduling scheme on grid environments
GCC'05 Proceedings of the 4th international conference on Grid and Cooperative Computing
Dynamic partitioning of loop iterations on heterogeneous PC clusters
The Journal of Supercomputing
Implementation of a Performance-Based Loop Scheduling on Heterogeneous Clusters
ICA3PP '09 Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing
Hi-index | 0.00 |
The effectiveness of loop self-scheduling schemes has been shown on traditional multiprocessors in the past and computing clusters in the recent years. However, parallel loop scheduling has not been widely applied to computing grids, which are characterized by heterogeneous resources and dynamic environments. In this paper, a performance-based approach, taking the two characteristics above into consideration, is proposed to schedule parallel loop iterations on grid environments. Furthermore, we use a parameter, SWR, to estimate the proportion of the workload which can be scheduled statically, thus alleviating the effect of irregular workloads. Experimental results on a grid testbed show that the proposed approach can reduce the completion time for applications with regular or irregular workloads. Consequently, we claim that parallel loop scheduling can benefit applications on grid environments.