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Application of neural-network methods for prediction of the job execution characteristics in multiprocessor computing systemsстатья
Информация о цитировании статьи получена из
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Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 24 мая 2016 г.
- Авторы: Goritskaya V.Yu, Popova N.N.
- Журнал: Moscow University Computational Mathematics and Cybernetics
- Том: 31
- Номер: 3
- Год издания: 2007
- Издательство: Allerton Press Inc.
- Местоположение издательства: United States
- Первая страница: 118
- Последняя страница: 122
- Аннотация: In recent years, the architecture of multiprocessor computing systems has become more and more complex and needs in large amounts of computations rapidly increase, together with the number of users of multiprocessor systems. Because of a large number of factors acting on the user job inside such a system, analytical approaches to solution of the job scheduling problem are very complex and expensive. This paper considers a neural-network approach to scheduling the computations in multiprocessor systems (which uses a method that predicts certain characteristics of the job execution procedure) and estimates the applicability of this approach in real conditions. Ways for increasing the accuracy of prediction are proposed.
- Добавил в систему: Попова Нина Николаевна