Performance of supercomputer depends on the quality of resource manager, one of its functions is assignment of jobs to the nodes of clusters or MPP computers. Parts of parallel programs interact with each other with different intensity, and mapping of program to supercomputer nodes influence efficiency of the run. At each program run graph representing application program is to be mapped onto graph of nodes representing a subset of computer system. The both graphs are not known beforehand, hence the mapping must be done in reasonable time while scheduling resources. Three mapping algorithms were explored: parallel versions of simulated annealing, genetic and composite algorithms. A set of experimental runs with different algorithms parameters was performed, comparison of mapping quality and runtime was made, and suggestions on applicability of algorithms for resource managers were provided.

翻译：超级计算机的性能取决于资源管理者的质量,其功能之一是将工作分配给集群或MPP计算机的节点,其部分平行程序以不同强度相互互动,将程序映射成超级计算机节点影响运行效率。每个程序运行的图示代表了应用程序的效率。每个程序运行的图示将映射到代表计算机系统子集的节点图上。这两个图图都是事先不为人知的,因此在安排资源时必须在合理的时间内进行绘图。探讨了三种绘图算法:模拟肛门、遗传和复合算法的平行版本。进行了一套带有不同算法参数的实验运行,比较了绘图质量和运行时间,并就算法对资源管理者的适用性提出了建议。