I/O benchmarking of data intensive applications

Abstract. The increasing computerization of the society over the last decade led to the increased data volumes stored over the world. The need to handle and store these massive amounts of data, arising from diverse sources as scientific records, web pages, or social networks has created a new class...

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Бібліографічні деталі
Дата:2010
Автори: Mordvinova, Olga, Ludwig, Thomas, Bartholomä, Christian
Формат: Стаття
Мова:Англійська
Опубліковано: Інститут програмних систем НАН України 2010
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Онлайн доступ:https://nasplib.isofts.kiev.ua/handle/123456789/14684
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Назва журналу:Digital Library of Periodicals of National Academy of Sciences of Ukraine
Цитувати:I/O benchmarking of data intensive applications/ Mordvinova Olga, Ludwig Thomas, Bartholomä Christian// Пробл. програмув. — 2010. — № 2-3. — С. 107-114. — Бібліогр.: 35 назв. — англ.

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Digital Library of Periodicals of National Academy of Sciences of Ukraine
Опис
Резюме:Abstract. The increasing computerization of the society over the last decade led to the increased data volumes stored over the world. The need to handle and store these massive amounts of data, arising from diverse sources as scientific records, web pages, or social networks has created a new class of application – data intensive applications. Usually designed up to the specific application requirements, one of these most challenging questions is choice of the appropriate back-end. The I/O benchmarking tools can easy this decision process. However, despite of its high variety, there is a lack of portable and easily adaptable benchmarks that can correspond to the real application behavior. The programmable I/O benchmark Parabench tries to close this gap. Its input is based on access patterns, which can be adjusted to the application, for which the system is to be used. Our work concentrates on ability of Parabench in mimicking real applications. We describe here its capabilities to handle MPI-I/O and POSIX and present a modeling example of a data intensive application from the field of business intelligence.
ISSN:1727-4907