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Интеллектуальная Система Тематического Исследования НАукометрических данных |
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On HPC & Cloud Environments Integration. Chapter 1статья
Информация о цитировании статьи получена из
Scopus
Дата последнего поиска статьи во внешних источниках: 13 ноября 2023 г.
- Авторы: Смелянский Р.Л., Антоненко В.А., Степанов Е.П., Чупахин А.А., Колосов А.М.
- Сборник: Performance evaluation models for distributed service networks
- Глава в коллективной монографии
- Год издания: 2020
- Место издания: Springer Springer Nature Switzerland AG Gewerbestrasse 11, 6330 Cham, Switzerland
- DOI: 10.1007/978-3-030-67063-4
- Аннотация: Recently in many scientific disciplines, e.g. physics, chemistry, biologyand multidisciplinary research have shifted to computational modelling. The maininstrument for such numerical experiments has been supercomputing. However, thenumber of supercomputers and their performance grows significantly slower thanthe growth of users’ demands. As a result, users of supercomputers may wait forweeks until their job will be done. At the same time the computational power ofcloud computing recently grows up considerably represented by heterogeneous DCnetwork with plenty of available resources for numerical experiments. In these circumstances,it may turn out that the time spent by the task in the system, i.e. the timespent in the queue + computing time, in the cloud environment may be shorter thanin HPC installation. There are several problems related to cloud and supercomputerenvironments integration. First, is how to make a decision where to send a computationaltask: to a supercomputer or to cloud. Secondly, these environments may havesignificantly different APIs, so moving a computational task from one environmentto another may require a lot of code modification. Another significant problem is anautomatic provisioning of virtual environment to execute the task properly. The thirdone is how to organize effectively migration data, computational tasks, applicationsand services in DC network, between DC and HPC installation? Saying effectively,we mean that network can allocate shortly, on demand, the necessary capacity in orderto transfer the necessary amount of data for the right time. It is called ‘Capacityon Demand’ service. In this chapter an environment for academic multidisciplinaryresearch – Meta Cloud Computing Environment (MC2E) is presented. This environmentdemonstrates the possible solutions and approaches to the problems listedabove.ISBN 978-3-030-67062-7
- Добавил в систему: Врагова Елена Юрьевна