Proceedings of the 2003 ACM/IEEE conference on Supercomputing
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
Agent-Based Load Balancing on Homogeneous Minigrids: Macroscopic Modeling and Characterization
IEEE Transactions on Parallel and Distributed Systems
Multiround Algorithms for Scheduling Divisible Loads
IEEE Transactions on Parallel and Distributed Systems
Adaptive multi-round scheduling strategy for divisible workloads in grid environments
ICOIN'09 Proceedings of the 23rd international conference on Information Networking
A distributed system for genetic linkage analysis
GCCB'06 Proceedings of the 2006 international conference on Distributed, high-performance and grid computing in computational biology
Application classification through monitoring and learning of resource consumption patterns
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
A methodology for dynamic scheduling of divisible workloads in grid environments
SMO'05 Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Inter-round scheduling for divisible workload applications
ICA3PP'05 Proceedings of the 6th international conference on Algorithms and Architectures for Parallel Processing
Multiresource allocation: fairness-efficiency tradeoffs in a unifying framework
IEEE/ACM Transactions on Networking (TON)
| Hi-index | 0.00 |
Divisible workload applications arise in many fields of science and engineering. They can be parallelized in master-worker fashion and relevant scheduling strategies have been proposed to reduce application makespan. Our goal is to develop a practical divisible workload scheduling strategy. This requires that previous work be revisited as several usual assumptions about the computing platform do not hold in practice. We have partially addressed this concern in a previous paper via an algorithm that achieves high performance with realistic resource latency models. In this paper we extend our approach to account for performance prediction errors, which are expected for most real-world performance and applications. In essence, we combine ideas from multi-round divisible workload scheduling,for performance, and from factoring-based scheduling, for robustness. We present simulation results to quantify the benefits of our approach compared to our original algorithm and to other previously proposed algorithms.