Modeling the benefits of mixed data and task parallelism
Proceedings of the seventh annual ACM symposium on Parallel algorithms and architectures
Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
A Low-Cost Approach towards Mixed Task and Data Parallel Scheduling
ICPP '02 Proceedings of the 2001 International Conference on Parallel Processing
Distributed Dynamic Scheduling of Composite Tasks on Grid Computing Systems
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Scheduling Distributed Applications: the SimGrid Simulation Framework
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
One-Step Algorithm for Mixed Data and Task Parallel Scheduling without Data Replication
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Critical Path and Area Based Scheduling of Parallel Task Graphs on Heterogeneous Platforms
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
A Comparison of Scheduling Approaches for Mixed-Parallel Applications on Heterogeneous Platforms
ISPDC '07 Proceedings of the Sixth International Symposium on Parallel and Distributed Computing
On cluster resource allocation for multiple parallel task graphs
Journal of Parallel and Distributed Computing
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Two of the main characteristics of computation grids are their heterogeneity and the sharing of resources between different users. This is the cost of the tremendous computing power offered by such platforms. Scheduling several applications concurrently in such an environment is thus challenging. In this paper we propose a first step towards the scheduling of multiple parallel task graphs (PTG), a class of applications that can benefit of large and powerful platforms, by focusing on the allocation process. We consider the application of a resource constraint on the schedule and determine the number of processors allocated to the different tasks of a PTG while respecting that constraint. We present two different allocation procedures and validate them in simulation over a wide range of scenarios with regard to their respect of the resource constraint and their impact on the completion time of the scheduled applications. We find that our procedures provide a guarantee on the resource usage for a low cost in terms of execution time.