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PARALLELISATION OF THE MODEL-BASED ITERATIVE RECONSTRUCTION ALGORITHM DIRA
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-9072-2204
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.ORCID iD: 0000-0003-3352-8330
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.ORCID iD: 0000-0003-0209-498X
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2015 (English)In: Radiation Protection Dosimetry, ISSN 0144-8420, E-ISSN 1742-3406, Vol. 169, no 1-4, 405-409 p.Article in journal (Refereed) Published
Abstract [en]

New paradigms for parallel programming have been devised to simplify software development on multi-core processors and many-core graphical processing units (GPU). Despite their obvious benefits, the parallelisation of existing computer programs is not an easy task. In this work, the use of the Open Multiprocessing (OpenMP) and Open Computing Language (OpenCL) frameworks is considered for the parallelisation of the model-based iterative reconstruction algorithm DIRA with the aim to significantly shorten the code’s execution time. Selected routines were parallelised using OpenMP and OpenCL libraries; some routines were converted from MATLAB to C and optimised. Parallelisation of the code with the OpenMP was easy and resulted in an overall speedup of 15 on a 16-core computer. Parallelisation with OpenCL was more difficult owing to differences between the central processing unit and GPU architectures. The resulting speedup was substantially lower than the theoretical peak performance of the GPU; the cause was explained.

Place, publisher, year, edition, pages
Oxford university press, 2015. Vol. 169, no 1-4, 405-409 p.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-123009DOI: 10.1093/rpd/ncv430PubMedID: 26454270OAI: oai:DiVA.org:liu-123009DiVA: diva2:875757
Funder
Swedish Cancer Society, CAN 2012/764Swedish Cancer Society, CAN 2014/691
Available from: 2015-12-01 Created: 2015-12-01 Last updated: 2016-07-15

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The full text will be freely available from 2016-10-09 20:11
Available from 2016-10-09 20:11

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Magnusson, MariaSandborg, MichaelAlm Carlsson, GudrunMalusek, Alexandr
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Division of Radiological SciencesCenter for Medical Image Science and Visualization (CMIV)Faculty of Medicine and Health SciencesComputer VisionFaculty of Science & EngineeringDepartment of Radiation Physics
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Radiation Protection Dosimetry
Computer Vision and Robotics (Autonomous Systems)

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