Improving the execution performance of FreeSurfer

A scheme to significantly speed up the processing of MRI with FreeSurfer (FS) is presented. The scheme is aimed at maximizing the productivity (number of subjects processed per unit time) for the use case of research projects with datasets involving many acquisitions. The scheme combines the already...

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Detalles Bibliográficos
Autores: Delgado, Jordi|||0000-0002-0166-5464, Moure, Juan C.|||0000-0001-6697-0331, Vives-Gilabert, Yolanda|||0000-0002-3744-5893, Delfino, Manuel|||0000-0002-9468-4751, Espinosa, Antonio|||0000-0002-6460-3789, Gómez Ansón, Beatriz|||0000-0001-7900-938X
Tipo de recurso: artículo
Fecha de publicación:2014
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:288059
Acceso en línea:https://ddd.uab.cat/record/288059
https://dx.doi.org/urn:doi:10.1007/s12021-013-9214-1
Access Level:acceso abierto
Palabra clave:FreeSurfer
MRI
Medical imaging
GPU
CUDA
Resource scheduler
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spelling Improving the execution performance of FreeSurferDelgado, Jordi|||0000-0002-0166-5464Moure, Juan C.|||0000-0001-6697-0331Vives-Gilabert, Yolanda|||0000-0002-3744-5893Delfino, Manuel|||0000-0002-9468-4751Espinosa, Antonio|||0000-0002-6460-3789Gómez Ansón, Beatriz|||0000-0001-7900-938XFreeSurferMRIMedical imagingGPUCUDAResource schedulerA scheme to significantly speed up the processing of MRI with FreeSurfer (FS) is presented. The scheme is aimed at maximizing the productivity (number of subjects processed per unit time) for the use case of research projects with datasets involving many acquisitions. The scheme combines the already existing GPU-accelerated version of the FS workflow with a task-level parallel scheme supervised by a resource scheduler. This allows for an optimum utilization of the computational power of a given hardware platform while avoiding problems with shortages of platform resources. The scheme can be executed on a wide variety of platforms, as its implementation only involves the script that orchestrates the execution of the workflow components and the FS code itself requires no modifications. The scheme has been implemented and tested on a commodity platform within the reach of most research groups (a personal computer with four cores and an NVIDIA GeForce 480 GTX graphics card). Using the scheduled task-level parallel scheme, a productivity above 0.6 subjects per hour is achieved on the test platform, corresponding to a speedup of over six times compared to the default CPU-only serial FS workflow.Port d'Informació Científica 22014-01-0120142014-01-01Articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://ddd.uab.cat/record/288059https://dx.doi.org/urn:doi:10.1007/s12021-013-9214-1reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengMinisterio de Ciencia e Innovación https://doi.org/10.13039/501100004837 TIN2011-28689-C02-01open accesshttp://purl.org/coar/access_right/c_abf2Aquest material està protegit per drets d'autor i/o drets afins. Podeu utilitzar aquest material en funció del que permet la legislació de drets d'autor i drets afins d'aplicació al vostre cas. Per a d'altres usos heu d'obtenir permís del(s) titular(s) de drets.https://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:2880592026-06-06T12:50:31Z
dc.title.none.fl_str_mv Improving the execution performance of FreeSurfer
title Improving the execution performance of FreeSurfer
spellingShingle Improving the execution performance of FreeSurfer
Delgado, Jordi|||0000-0002-0166-5464
FreeSurfer
MRI
Medical imaging
GPU
CUDA
Resource scheduler
title_short Improving the execution performance of FreeSurfer
title_full Improving the execution performance of FreeSurfer
title_fullStr Improving the execution performance of FreeSurfer
title_full_unstemmed Improving the execution performance of FreeSurfer
title_sort Improving the execution performance of FreeSurfer
dc.creator.none.fl_str_mv Delgado, Jordi|||0000-0002-0166-5464
Moure, Juan C.|||0000-0001-6697-0331
Vives-Gilabert, Yolanda|||0000-0002-3744-5893
Delfino, Manuel|||0000-0002-9468-4751
Espinosa, Antonio|||0000-0002-6460-3789
Gómez Ansón, Beatriz|||0000-0001-7900-938X
author Delgado, Jordi|||0000-0002-0166-5464
author_facet Delgado, Jordi|||0000-0002-0166-5464
Moure, Juan C.|||0000-0001-6697-0331
Vives-Gilabert, Yolanda|||0000-0002-3744-5893
Delfino, Manuel|||0000-0002-9468-4751
Espinosa, Antonio|||0000-0002-6460-3789
Gómez Ansón, Beatriz|||0000-0001-7900-938X
author_role author
author2 Moure, Juan C.|||0000-0001-6697-0331
Vives-Gilabert, Yolanda|||0000-0002-3744-5893
Delfino, Manuel|||0000-0002-9468-4751
Espinosa, Antonio|||0000-0002-6460-3789
Gómez Ansón, Beatriz|||0000-0001-7900-938X
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Port d'Informació Científica
dc.subject.none.fl_str_mv FreeSurfer
MRI
Medical imaging
GPU
CUDA
Resource scheduler
topic FreeSurfer
MRI
Medical imaging
GPU
CUDA
Resource scheduler
description A scheme to significantly speed up the processing of MRI with FreeSurfer (FS) is presented. The scheme is aimed at maximizing the productivity (number of subjects processed per unit time) for the use case of research projects with datasets involving many acquisitions. The scheme combines the already existing GPU-accelerated version of the FS workflow with a task-level parallel scheme supervised by a resource scheduler. This allows for an optimum utilization of the computational power of a given hardware platform while avoiding problems with shortages of platform resources. The scheme can be executed on a wide variety of platforms, as its implementation only involves the script that orchestrates the execution of the workflow components and the FS code itself requires no modifications. The scheme has been implemented and tested on a commodity platform within the reach of most research groups (a personal computer with four cores and an NVIDIA GeForce 480 GTX graphics card). Using the scheduled task-level parallel scheme, a productivity above 0.6 subjects per hour is achieved on the test platform, corresponding to a speedup of over six times compared to the default CPU-only serial FS workflow.
publishDate 2014
dc.date.none.fl_str_mv 2
2014-01-01
2014
2014-01-01
dc.type.none.fl_str_mv Article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://ddd.uab.cat/record/288059
https://dx.doi.org/urn:doi:10.1007/s12021-013-9214-1
url https://ddd.uab.cat/record/288059
https://dx.doi.org/urn:doi:10.1007/s12021-013-9214-1
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Ciencia e Innovación https://doi.org/10.13039/501100004837 TIN2011-28689-C02-01
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
reponame_str Dipòsit Digital de Documents de la UAB
collection Dipòsit Digital de Documents de la UAB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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