Abstract: The resources allocation for heterogeneous multi-cores is modeled as a three dimensional optimization space. Each element in the optimization space corresponds to a parallelization scheme. Finding efficient parallelization schemes for a multi-task program is to explore this search space. In order to accelerate space exploration, an intelligent search based on genetic algorithm is adapted. Experiments show that the model-driven approach can derive good parallelization schemes in very short time.

Key words: heterogeneous multi-core processors, resource allocation model, optimization space exploration, genetic algorithm

摘要： 将异构多核处理器的资源分配问题抽象为一个三维优化空间，空间中的每个元素对应多任务程序的一个并行策略，确定程序有效并行策略的问题转化为优化空间的搜索问题。为了加速搜索，提出一种基于遗传算法的智能搜索方法。实验表明，模型驱动的并行策略选择方法能够在极短的时间内为程序生成较好的并行策略。

关键词: 异构多核处理器, 资源分配模型, 优化搜索空间, 遗传算法