MagPIe: MPI's collective communication operations for clustered wide area systems
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Future Generation Computer Systems
The distributed ASCI Supercomputer project
ACM SIGOPS Operating Systems Review
Enhanced Algorithms for Multi-site Scheduling
GRID '02 Proceedings of the Third International Workshop on Grid Computing
Characteristics of a Large Shared Memory Production Workload
JSSPP '01 Revised Papers from the 7th International Workshop on Job Scheduling Strategies for Parallel Processing
Resource Co-allocation for Parallel Tasks in Computational Grids
CLADE '03 Proceedings of the 1st International Workshop on Challenges of Large Applications in Distributed Environments
Resource Co-Allocation in Computational Grids
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
On Advantages of Grid Computing for Parallel Job Scheduling
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
Optimizing Parallel Applications for Wide-Area Clusters
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
Bandwidth-aware co-allocating meta-schedulers for mini-grid architectures
CLUSTER '04 Proceedings of the 2004 IEEE International Conference on Cluster Computing
An evaluation of the close-to-files processor and data co-allocation policy in multiclusters
CLUSTER '04 Proceedings of the 2004 IEEE International Conference on Cluster Computing
Experiences with the KOALA co-allocating scheduler in multiclusters
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
Rescheduling co-allocation requests based on flexible advance reservations and processor remapping
GRID '08 Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing
Future Generation Computer Systems
New challenges of parallel job scheduling
JSSPP'07 Proceedings of the 13th international conference on Job scheduling strategies for parallel processing
Deadline-guarantee-enhanced co-allocation for parameter sweep application in grid
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Predicting vertebrate promoters using heterogeneous clusters
International Journal of Ad Hoc and Ubiquitous Computing
The Journal of Supercomputing
Adaptive Executions of Multi-Physics Coupled Applications on Batch Grids
Journal of Grid Computing
The Journal of Supercomputing
Concurrency and Computation: Practice & Experience
MIP model scheduling for multi-clusters
Euro-Par'12 Proceedings of the 18th international conference on Parallel processing workshops
State-based predictions with self-correction on Enterprise Desktop Grid environments
Journal of Parallel and Distributed Computing
Resource co-allocation framework based on hybrid gaming model in grid environments
International Journal of Grid and Utility Computing
International Journal of Computational Science and Engineering
Hi-index | 0.00 |
Building multicluster systems out of multiple, geographically distributed clusters interconnected by high-speed wide-area networks can provide access to a larger computational power and to a wider range of resources. Jobs running on multiclusters and, more generally, in grids, may require (processor) coallocation, i.e., the simultaneous allocation of resources (processors) in different clusters or subsystems of a grid. In this paper, we propose four scheduling policies for processor coallocation in multiclusters, and we assess with simulations their performance under a wide variety of parameter settings. In particular, in our simulations we use synthetic workloads and workloads derived from the logs of actual systems and from runtime measurements. We conclude that although coallocation makes scheduling more difficult and the wide-area communication critically impacts the performance, there is a wide range of realistic applications that may benefit from coallocation. However, unrestricted coallocation is not recommended: Limiting the total job size or the number or the sizes of their components improves performance.