Experiences with Cell-BE and GPU for Tomography

Authors:
Sander Maar;Kees Joost Batenburg;Jan Sijbers
Affiliations:
IBBT-Vision Lab, Department of Physics, University of Antwerp, Belgium;IBBT-Vision Lab, Department of Physics, University of Antwerp, Belgium;IBBT-Vision Lab, Department of Physics, University of Antwerp, Belgium
Venue:
SAMOS '09 Proceedings of the 9th International Workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation
Year:
2009

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Abstract

Tomography is a powerful technique for three-dimensional imaging, that deals with image reconstruction from a series of projection images, acquired along a range of viewing directions. An important part of any tomograph system is the reconstruction algorithm . Iterative reconstruction algorithms have many advantages over non-iterative methods, yet their running time can be prohibitively long. As these algorithms have high potential for parallelization, multi-core architectures, such as the Cell-BE and GPU, can possibly alleviate this problem. In this paper, we describe our experiences in mapping the basic operations of iterative reconstruction algorithms onto these platforms. We argue that for this type of problem, the GPU yields superior performance compared to the Cell-BE. Performance results of our implementation demonstrate a speedup of over 40 for a single GPU, compared to a single-core CPU version. By combining eight GPUs and a quad-core CPU in a single system, similar performance to a large cluster consisting of hundreds of CPU cores has been obtained.