关键词: 异构多核处理器（CMP）, 任务调度, 蚁群算法, 遗传算法

Abstract: In order to improve the efficiency of task scheduling for heterogeneous Chip Multi-core Processor, this paper proposes an improved ant colony optimization algorithm for task scheduling on heterogeneous CMP, called IACOTS, to exploit the power of heterogeneity and parallel capability of heterogeneous CMP. IACOTS algorithm creates a new task scheduling model and path selection rules. The ACO can be applied to discrete heterogeneous CMP task scheduling problem. Meanwhile, it uses dynamic pheromone updating, two ant parallel search strategy, and the variations factor of genetic algorithm, to overcome the ACO to search too long and “premature” convergence phenomenon, improving local search speed and reducing the total program execution time. The results obtained through simulation experiments show that the algorithm has good performance of global optimization, and distributed parallel computer system. The performance is better than existing heterogeneous multiprocessor task scheduling algorithm.

Key words: heterogeneous Chip Multi-core Processor, task scheduling, ant colony algorithm, genetic algorithm