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.
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© 2009 IFIP International Federation for Information Processing
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van der Maar, S., Batenburg, K.J., Sijbers, J. (2009). Experiences with Cell-BE and GPU for Tomography. In: Bertels, K., Dimopoulos, N., Silvano, C., Wong, S. (eds) Embedded Computer Systems: Architectures, Modeling, and Simulation. SAMOS 2009. Lecture Notes in Computer Science, vol 5657. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03138-0_33
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DOI: https://doi.org/10.1007/978-3-642-03138-0_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03137-3
Online ISBN: 978-3-642-03138-0
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