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Experiences with Cell-BE and GPU for Tomography

  • Sander van der Maar
  • Kees Joost Batenburg
  • Jan Sijbers
Conference paper
  • 591 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5657)

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.

Keywords

Memory Access Iterative Reconstruction Graphic Hardware Iterative Reconstruction Algorithm Forward Projection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Sander van der Maar
    • 1
  • Kees Joost Batenburg
    • 1
  • Jan Sijbers
    • 1
  1. 1.IBBT-Vision Lab, Department of PhysicsUniversity of AntwerpBelgium

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