Journal of Parallel and Distributed Computing
Allocating Modules to Processors in a Distributed System
IEEE Transactions on Software Engineering
Computer
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
SmartNet: a scheduling framework for heterogeneous computing
ISPAN '96 Proceedings of the 1996 International Symposium on Parallel Architectures, Algorithms and Networks
Adaptive Computing on the Grid Using AppLeS
IEEE Transactions on Parallel and Distributed Systems
On the Robustness Of Metaprogram Schedules
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
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Heterogeneous computing covers a great variety of situations. This study focuses on a particular application domain (iterative automatic target recognition tasks) and an associated specific class of dedicated heterogeneous hardware platforms. The contribution of this paper is that, for the computational environment considered, it presents a methodology for real-time on-line input-data dependent remappings of the application subtasks to the processors in the heterogeneous hardware platform using previously stored off-line statically determined mappings. That is, the operating system will be able to decide during the execution of the application whether or not to perform a remapping based on information generated by the application from its input data. If the decision is to remap, the operating system will be able to select a previously derived and stored mapping that is appropriate for the given state of the application (e.g., the number of objects it is currently tracking).