Static vs. Dynamic List-Scheduling Performance Comparison

The problem of efficient task scheduling is one of the most important and most difficult issues in homogeneous computing environments. Finding an optimal solution for a scheduling problem is NP-complete. Therefore, it is necessary to have heuristics to find a reasonably good schedule rather than evaluate all possible schedules. List-scheduling is generally accepted as an attractive approach, since it pairs low complexity with good results. List-scheduling algorithms schedule tasks in order of priority. This priority can be computed either statically (before scheduling) or dynamically (during scheduling). This paper presents the characteristics of the two main static and the two main dynamic list-scheduling algorithms. It also compares their performance in dealing with random generated graphs with various characteristics

Иерархический способ планирования для GRID

Paper is devoted to increasing of Grid systems real performance by effective scheduling method using. We propose an improved hierarchical scheduling method that uses one of the three optimization criterion determined by user. This method efficiency provides by creation of the new list scheduling algorithms for homogeneous and heterogeneous Grid system nodes and creation of task graph transformation.Статья посвящена повышению пользовательской производительности Grid систем за счет более эффективного способа планирования вычислений. Предложен усовершенствованный иерархический способ планирования, ориентированный на один из трех критериев оптимизации по выбору пользователя. Эффективность данного способа обеспечивается за счет разработанных авторами списочных алгоритмов для однородных и неоднородных узлов Grid систем, а также предложенных способов трансформации графов задач

List scheduling revisited

We consider the problem of scheduling n jobs on m identical parallel machines to minimize a regular cost function. The standard list scheduling algorithm converts a list into a feasible schedule by focusing on the job start times. We prove that list schedules are dominant for this type of problem. Furthermore, we prove that an alternative list scheduling algorithm, focusing on the completion times rather than the start times, yields also dominant list schedules for problems with sequence dependent setup times

A Comparison of Scheduling Approaches for Mixed-Parallel Applications on Heterogeneous Platforms

International audienceMixed-parallel applications can take advantage of large-scale computing platforms but scheduling them efficiently on such platforms is challenging. In this paper we compare the two main proposed approaches for solving this scheduling problem on a heterogeneous set of homogeneous clusters. We first modify previously proposed algorithms for both approaches and show that our modifications lead to significant improvements. We then perform a comparison of the modified algorithms in simulation over a wide range of application and platform conditions. We find that although both approaches have advantages, one of them is most likely he most appropriate for the majority of users