On the scalability and dynamic load-balancing of optimistic gate level simulation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A Multi-State Q-Learning Approach for the Dynamic Load Balancing of Time Warp
PADS '10 Proceedings of the 2010 IEEE Workshop on Principles of Advanced and Distributed Simulation
A load index and load balancing algorithm for heterogeneous clusters
The Journal of Supercomputing
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In order to balance loadings in heterogenous parallel processing systems, a new task scheduling algorithm, weighted least connection genetic algorithm (WLGA), is proposed. WLGA algorithm uses the genetic algorithm to improve the weighted least connection algorithm (WLCA), it overcomes deficiencies of WLCA algorithms and provides functions of dynamic control to schedule tasks so that the distribution problem of N processors is solved effectively. The experimental result shows the improved algorithm WLGA is superior to basic genetic algorithm and WLCA algorithm.