| Literature DB >> 28658599 |
Jesús Cuenca-Alba1, Laura Del Cano2, Josué Gómez Blanco2, José Miguel de la Rosa Trevín2, Pablo Conesa Mingo2, Roberto Marabini3, Carlos Oscar S Sorzano2, Jose María Carazo2.
Abstract
New instrumentation for cryo electron microscopy (cryoEM) has significantly increased data collection rate as well as data quality, creating bottlenecks at the image processing level. Current image processing model of moving the acquired images from the data source (electron microscope) to desktops or local clusters for processing is encountering many practical limitations. However, computing may also take place in distributed and decentralized environments. In this way, cloud is a new form of accessing computing and storage resources on demand. Here, we evaluate on how this new computational paradigm can be effectively used by extending our current integrative framework for image processing, creating ScipionCloud. This new development has resulted in a full installation of Scipion both in public and private clouds, accessible as public "images", with all the required preinstalled cryoEM software, just requiring a Web browser to access all Graphical User Interfaces. We have profiled the performance of different configurations on Amazon Web Services and the European Federated Cloud, always on architectures incorporating GPU's, and compared them with a local facility. We have also analyzed the economical convenience of different scenarios, so cryoEM scientists have a clearer picture of the setup that is best suited for their needs and budgets.Keywords: Cloud computing; Cryo-electron microscopy; Distributed computing
Mesh:
Year: 2017 PMID: 28658599 DOI: 10.1016/j.jsb.2017.06.004
Source DB: PubMed Journal: J Struct Biol ISSN: 1047-8477 Impact factor: 2.867