Journal of Parallel and Distributed Computing
Allocating Modules to Processors in a Distributed System
IEEE Transactions on Software Engineering
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Computer
Software support for heterogeneous computing
ACM Computing Surveys (CSUR)
Journal of Parallel and Distributed Computing - Special issue on parallel evolutionary computing
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Implementations of a Feature-Based Visual Tracking Algorithm on Two MIMD Machines Mark Bernd
ICPP '97 Proceedings of the international Conference on Parallel Processing
Mercury Computer Systems' modular heterogeneous RACE(R) multicomputer
HCW '97 Proceedings of the 6th Heterogeneous Computing Workshop (HCW '97)
SmartNet: a scheduling framework for heterogeneous computing
ISPAN '96 Proceedings of the 1996 International Symposium on Parallel Architectures, Algorithms and Networks
Theory and practice in system-level design of application-specific heterogeneous multiprocessors
Theory and practice in system-level design of application-specific heterogeneous multiprocessors
An Overview of MSHN: The Management System for Heterogeneous Networks
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
A semi-static approach to mapping dynamic iterative tasks onto heterogeneous computing systems
Journal of Parallel and Distributed Computing
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This study focuses on a particular application domain (iterativeautomatic target recognition tasks) and an associated specific class ofdedicated heterogeneous parallel hardware platforms. For thecomputational environment considered, a methodology is presented forthe on-line operating system to decide heuristically whether to performa remapping of the application onto the platform based on informationgenerated from input data by the application during execution. If thedecision is to remap, the operating system will be able to select amapping, which is appropriate for the given state of the application,from a stored set of mappings that were previously derived with anoff-line heuristic.