Empirical Study of Variable Granularity and Global Centralized Load Balancing Algorithms
نویسندگان
چکیده
Task migration and load sharing algorithms are two load balancing strategies that are essential in distributed memory multiprocessor as well as in multicomputer environments. Dynamic load balancing is more suitable in heterogeneous systems. Various load sharing and global centralized algorithms have been proposed in the literature. These algorithms demand careful investigation about their suitability in different applications. In this research paper we focus on the performance evaluation of two algorithms implemented on SPMD model based on their controlling parameters. A network of workstations has been chosen and PVM libraries have been used for implementation. Matrix multiplication has been selected as the application. The two algorithms investigated are: variable granularity (guided self scheduling) and one global centralized task migration algorithm.
منابع مشابه
Performance Evaluation of Three Dynamic Load Balancing Algorithms on Spmd Model
In this research paper, we focus on the performance of different task migration and load balancing algorithms on SPMD model based on their controlling parameters. A network of workstations has been chosen and PVM libraries have been used for implementation. Matrix multiplication has been selected as the application. Three algorithms have been investigated namely, fixed granularity, variable gra...
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