A Performance Study of GA and LSH in Multiprocessor Job Scheduling

Multiprocessor task scheduling is an important and computationally difficult problem. This paper proposes a comparison study of genetic algorithm and list scheduling algorithm. Both algorithms are naturally parallelizable but have heavy data dependencies. Based on experimental results, this paper presents a detailed analysis of the scalability, advantages and disadvantages of each algorithm. Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uni-processor system would not be sufficient enough to execute all the tasks. The high performance and reliability of multiprocessors have made them a powerful computing resource. Such computing environment requires an efficient algorithm to determine when and on which processor a given task should execute. In multiprocessor systems, an efficient scheduling of a parallel program onto the processors that minimizes the entire execution time is vital for achieving a high performance. This...

• Type: Journal
• Year: 2010
• Where: CORR
• Authors: S. R. Vijayalakshmi, G. Padmavathi
• Keywords: Algorithm, CORR 2010, Education, Genetic Algorithms, List Scheduling