guest ::
| Home > Publications database > Computation of Mutual Information Metric for Image Registration on Multiple GPUs > print |
| Home > Publications database > Computation of Mutual Information Metric for Image Registration on Multiple GPUs > print |
| 001 | 153430 | ||
| 005 | 20210129213735.0 | ||
| 020 | _ | _ | |a 978-3-642-54419-4 (print) |
| 020 | _ | _ | |a 978-3-642-54420-0 (electronic) |
| 024 | 7 | _ | |a 10.1007/978-3-642-54420-0_21 |2 doi |
| 024 | 7 | _ | |a 1611-3349 |2 ISSN |
| 024 | 7 | _ | |a 0302-9743 |2 ISSN |
| 037 | _ | _ | |a FZJ-2014-03047 |
| 082 | _ | _ | |a 004 |
| 100 | 1 | _ | |a Adinets, Andrey |0 P:(DE-Juel1)157723 |b 0 |e Corresponding Author |u fzj |
| 111 | 2 | _ | |a Euro-Par 2013: Parallel Processing Workshops |c Aachen |d 2013-08-25 - 2013-08-30 |w Germany |
| 245 | _ | _ | |a Computation of Mutual Information Metric for Image Registration on Multiple GPUs |
| 260 | _ | _ | |a Berlin, Heidelberg |c 2014 |b Springer Berlin Heidelberg |
| 295 | 1 | 0 | |a Euro-Par 2013: Parallel Processing Workshops |
| 300 | _ | _ | |a 208 - 217 |
| 336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1399528593_3032 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Contribution to a book |0 PUB:(DE-HGF)7 |2 PUB:(DE-HGF) |m contb |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Output Types/Conference Paper |2 DataCite |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 490 | 0 | _ | |a Lecture Notes in Computer Science |v 8374 |
| 520 | _ | _ | |a Because of their computational power, GPUs are widely used in the field of image processing. Registration of brain images has already been successfully accelerated with GPUs, but registration of high-resolution human brain images presents new challenges due to large amounts of data and images not fitting in the memory of a single device.In this paper, we address this issue with two approaches. The first approach replicates image data in system memory of each node and distributes only a part of the data over multiple GPUs. The second approach splits image data between multiple GPUs, and overlaps computation and communication to hide latency. For both approaches, we present a performance analysis and comparison. |
| 536 | _ | _ | |a 41G - Supercomputer Facility (POF2-41G21) |0 G:(DE-HGF)POF2-41G21 |c POF2-41G21 |f POF II |x 0 |
| 536 | _ | _ | |a SMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017) |0 G:(DE-Juel1)HGF-SMHB-2013-2017 |c HGF-SMHB-2013-2017 |f SMHB |x 1 |
| 588 | _ | _ | |a Dataset connected to CrossRef Book, juser.fz-juelich.de |
| 700 | 1 | _ | |a Kraus, Jiri |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Axer, Markus |0 P:(DE-Juel1)131632 |b 2 |u fzj |
| 700 | 1 | _ | |a Huysegoms, Marcel |0 P:(DE-Juel1)138708 |b 3 |u fzj |
| 700 | 1 | _ | |a Köhnen, Stefan |0 P:(DE-Juel1)157789 |b 4 |u fzj |
| 700 | 1 | _ | |a Pleiter, Dirk |0 P:(DE-Juel1)144441 |b 5 |u fzj |
| 773 | _ | _ | |a 10.1007/978-3-642-54420-0_21 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/153430/files/FZJ-2014-03047.pdf |y Restricted |
| 909 | C | O | |o oai:juser.fz-juelich.de:153430 |p VDB |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)157723 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)131632 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |6 P:(DE-Juel1)138708 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)157789 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 5 |6 P:(DE-Juel1)144441 |
| 913 | 2 | _ | |a DE-HGF |b Key Technologies |l Supercomputing & Big Data |1 G:(DE-HGF)POF3-510 |0 G:(DE-HGF)POF3-513 |2 G:(DE-HGF)POF3-500 |v Supercomputer Facility |x 0 |
| 913 | 1 | _ | |a DE-HGF |b Schlüsseltechnologien |l Supercomputing |1 G:(DE-HGF)POF2-410 |0 G:(DE-HGF)POF2-41G21 |2 G:(DE-HGF)POF2-400 |v Supercomputer Facility |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF2 |
| 914 | 1 | _ | |y 2014 |
| 915 | _ | _ | |a No Peer review |0 StatID:(DE-HGF)0020 |2 StatID |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Thomson Reuters Master Journal List |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
| 915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |
| 920 | _ | _ | |l no |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-1-20090406 |k INM-1 |l Strukturelle und funktionelle Organisation des Gehirns |x 1 |
| 980 | _ | _ | |a contrib |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a contb |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-1-20090406 |
| 980 | _ | _ | |a UNRESTRICTED |
| 981 | _ | _ | |a I:(DE-Juel1)INM-1-20090406 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|