Please use this identifier to cite or link to this item:
doi:10.22028/D291-26241
Title: | High performance cluster computing with 3-D nonlinear diffusion filters |
Author(s): | Bruhn, Andrés Jakob, Tobias Fischer, Markus Kohlberger, Timo Weickert, Joachim Brüning, Ulrich Schnörr, Christoph |
Language: | English |
Year of Publication: | 2003 |
Free key words: | additive operator splitting cluster computing |
DDC notations: | 510 Mathematics |
Publikation type: | Other |
Abstract: | This paper deals with parallelisation and implementation aspects of PDE-based image processing models for large cluster environments with distributed memory. As an example we focus on nonlinear diffusion filtering which we discretise by means of an additive operator splitting (AOS). We start by decomposing the algorithm into small modules that shall be parallelised separately. For this purpose image partitioning strategies are discussed and their impact on the communication pattern and volume is analysed. Based on the results we develop an algorithmic implementation with excellent scaling properties on massively connected low latency networks. Test runs on a high-end Myrinet cluster yield almost linear speedup factors up to 209 for 256 processors. This results in typical denoising times of 0.5 seconds for five iterations on a 256 x 256 x 128 data cube. |
Link to this record: | urn:nbn:de:bsz:291-scidok-44330 hdl:20.500.11880/26297 http://dx.doi.org/10.22028/D291-26241 |
Series name: | Preprint / Fachrichtung Mathematik, Universität des Saarlandes |
Series volume: | 87 |
Date of registration: | 4-Jan-2012 |
Faculty: | MI - Fakultät für Mathematik und Informatik |
Department: | MI - Mathematik |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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File | Description | Size | Format | |
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preprint_87_03.pdf | 371,38 kB | Adobe PDF | View/Open |
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