Papers Papers/2020



Paper Unlock

Authors: Ali Gholami 1 ; Gert Svensson 1 ; Erwin Laure 1 ; Matthias Eickhoff 2 and Götz Brasche 2

Affiliations: 1 Royal Institute of Technology, Sweden ; 2 Microsoft Research – Advanced Technology Labs (ATL) Europe, Germany

ISBN: 978-989-8565-52-5

ISSN: 2184-5042

Keyword(s): Cloud Computing, SPM, Microsoft Azure, e-Science as a Service, Brain Imaging, FMRI.

Related Ontology Subjects/Areas/Topics: Cloud Application Architectures ; Cloud Application Scalability and Availability ; Cloud Computing ; Cloud Middleware Frameworks ; Platforms and Applications

Abstract: The use of cloud computing as a new paradigm has become a reality. Cloud computing leverages the use of on-demand CPU power and storage resources while eliminating the cost of commodity hardware ownership. Cloud computing is now gaining popularity among many different organizations and commercial sectors. In this paper, we present the scalable brain image analysis (ScaBIA) architecture, a new model to run statistical parametric analysis (SPM) jobs using cloud computing. SPM is one of the most popular toolkits in neuroscience for running compute-intensive brain image analysis tasks. However, issues such as sharing raw data and results, as well as scalability and performance are major bottlenecks in the “single PC”-execution model. In this work, we describe a prototype using the generic worker (GW), an e-Science as a service middleware, on top of Microsoft Azure to run and manage the SPM tasks. The functional prototype shows that ScaBIA provides a scalable framework for multi-job submi ssion and enables users to share data securely using storage access keys across different organizations. (More)


Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Gholami, A.; Svensson, G.; Laure, E.; Eickhoff, M. and Brasche, G. (2013). ScaBIA: Scalable Brain Image Analysis in the Cloud . In Proceedings of the 3rd International Conference on Cloud Computing and Services Science - CLOSER, ISBN 978-989-8565-52-5; ISSN 2184-5042, pages 329-336. DOI: 10.5220/0004358003290336

author={Ali Gholami. and Gert Svensson. and Erwin Laure. and Matthias Eickhoff. and Götz Brasche.},
title={ScaBIA: Scalable Brain Image Analysis in the Cloud },
booktitle={Proceedings of the 3rd International Conference on Cloud Computing and Services Science - CLOSER,},


JO - Proceedings of the 3rd International Conference on Cloud Computing and Services Science - CLOSER,
TI - ScaBIA: Scalable Brain Image Analysis in the Cloud
SN - 978-989-8565-52-5
IS - 2184-5042
AU - Gholami, A.
AU - Svensson, G.
AU - Laure, E.
AU - Eickhoff, M.
AU - Brasche, G.
PY - 2013
SP - 329
EP - 336
DO - 10.5220/0004358003290336

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.