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Detalle de: Matrix Implementation of Simultaneous Iterative Reconstruction Technique (SIRT) on GPUs

Title Matrix Implementation of Simultaneous Iterative Reconstruction Technique (SIRT) on GPUs
Abstract

Electron tomography (ET) is an important technique in biosciences that is providing new insights into the cellular ultrastructure. Iterative reconstruction methods have been shown to be robust against the noise and limited-tilt range conditions present in ET. Nevertheless, these methods are not extensively used due to their computational demands. Instead, the simpler method weighted backprojection (WBP) remains prevalent. Recently, we have demonstrated that a matrix approach to WBP allows a significant reduction in processing time both on central processing units and on graphics processing units (GPUs). In this work, we extend that matrix approach to one of the most common iterative methods in ET, simultaneous iterative reconstruction technique (SIRT). We show that it is possible to implement this method targeted at GPU directly, using sparse algebra. We also analyse this approach on different GPU platforms and confirm that these implementations exhibit high performance. This may thus help to the widespread use of SIRT.

Apa Reference Vazquez, F., Garzon, E.M. & Fernandez, J.J. (2011). Matrix Implementation of Simultaneous Iterative Reconstruction Technique (SIRT) on GPUs. The Computer Journal, 54(11), 1861-1868. 10.1093/comjnl/bxr033
Doi 10.1093/comjnl/bxr033
Publication Date 20 Apr 2011
Publication Type Article
Researcher Jose-Jesus Fernandez
Ontology Experimental structure determination, Parallel Computing
Research Groups
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