High Performance Scientific Computing over Hybrid Cloud Platforms

Abstract

"Croyez ceux qui cherchent la vérité, doutez de ceux qui la trouvent." "Cree a aquellos que buscan la verdad. Duda de los que la han encontrado" André Gide (1952).iii AbstractScientific applications generally require large computational requirements, memory and data management for their execution. Such applications have traditionally used high-performance resources, such as shared memory supercomputers, clusters of PCs with distributed memory, or resources from Grid infrastructures on which the application needs to be adapted to run successfully. In recent years, the advent of virtualization techniques, together with the emergence of Cloud Computing, has caused a major shift in the way these applications are executed. However, the execution management of scientific applications on high performance elastic platforms is not a trivial task.

Cloud resource MathBrain for encephalography data analysis

“…При создании гибридной инфраструктуры [16] (использование как локальных аппаратных мощностей, так и публичных ресурсов), создается один или несколько контейнеров в публичном облаке. После отработки задачи, такой контейнер удаляется.…”