ИСПОЛЬЗОВАНИЕ ГЕТЕРОГЕННЫХ ВЫЧИСЛИТЕЛЬНЫХ УЗЛОВ В ГРИД-СИСТЕМАХ ПРИ РЕШЕНИИ КОМБИНАТОРНЫХ ЗАДАЧ

Abstract

The main goal of this work is to create a parallel application that performs computationsusing a multithreaded execution model, optimized to make the best utilization of all availablehardware resources. One of the main implementation requirements is to optimize application performanceon different computer architectures, and to enable parallel execution of the applicationon various computing devices that are part of a heterogeneous computing system. The possibilityof applying various methods of software and algorithmic optimization on multiprocessor architecturesof different generations was investigated as well as the effectiveness of their use for highlyloaded multithreaded applications was estimated. The problem of quasi-optimal dynamic distributionof computational tasks among all currently available computing devices of a heterogeneouscomputing system was also solved. Currently, not only multiprocessor computing systems are usedto solve large computational problems, but also various types of distributed systems. Distributedcomputing systems have a number of features: possible failures of nodes and communicationchannels, unstable operating time of nodes, possible errors in calculations, heterogeneity of computingnodes. By heterogeneity of computing nodes, we will understand not only the different computingcapacity and different architectures of central processors, but also the presence of otherdevices on the node capable of performing calculations. Such devices include video cards andmathematical coprocessors. A node of a distributed computing system will be called heterogeneousif, in addition to one or more central processing units, it contains additional computing devices.When solving a computational problem on a distributed system, it is necessary to maximize theutilization of all available computing resources. To do this, it is necessary not only to distributecomputing subtasks to nodes in accordance with their computing capacity, but also to take intoaccount the features of additional computing devices. This work is devoted to the study of methodsfor maximizing the resources utilization of heterogeneous nodes.