A projection-based data partitioning method for distributed tomographic reconstruction

Society for Industrial and Applied Mathematics eBooks, pp. 58–68

Abstract

Tomography is a non-destructive technique for imaging the interior of a 3D object. We present an efficient data partitioning strategy for distributed tomographic reconstruction algorithms. Our novel partitioning method is a refinement of the previously published GRCB algorithm. Instead of taking as input a discrete set of lines corresponding to source-pixel pairs, the introduced algorithm works directly on the (cone-shaped) projections. We introduce a geometric characterization of the communication volume, as well as a continuous model for load-balancing based on the varying line densities throughout the object volume. The resulting algorithm is orders of magnitude faster than the original algorithm while producing partitionings of similar quality. We introduce a novel communication data structure that can efficiently represent the communication metadata. An implementation on top of Bulk and the ASTRA toolbox is discussed. We provide experimental results of our method for various commonly used acquisition geometries. We achieve a speedup of 2.8× compared to ASTRA-MPI when using 32 GPUs to reconstruct an image for a circular-cone beam acquisition geometry.

Authors 4

1. Jan‐Willem Buurlage Aachen Mathematical Institute

   Leiden University · Centrum Wiskunde & Informatica · Utrecht University

   Affiliation as printed

   Centrum Wiskunde & Informatica, PO Box 94079, 1090 GB Amsterdam, the Netherlands

   Mathematical Institute, Leiden University, PO Box 9512, 2300 RA Leiden, the Netherlands

   Mathematical Institute, Utrecht University, PO Box 80010, 3508 TA Utrecht, the Netherlands

2. Rob H. Bisseling
3. Willem Jan Palenstijn Aachen Mathematical Institute

   Leiden University · Centrum Wiskunde & Informatica · Utrecht University

   Affiliation as printed

   Centrum Wiskunde & Informatica, PO Box 94079, 1090 GB Amsterdam, the Netherlands

   Mathematical Institute, Leiden University, PO Box 9512, 2300 RA Leiden, the Netherlands

   Mathematical Institute, Utrecht University, PO Box 80010, 3508 TA Utrecht, the Netherlands

4. Kees Joost Batenburg Aachen Mathematical Institute

   Leiden University · Centrum Wiskunde & Informatica · Utrecht University

   Affiliation as printed

   Centrum Wiskunde & Informatica, PO Box 94079, 1090 GB Amsterdam, the Netherlands

   Mathematical Institute, Leiden University, PO Box 9512, 2300 RA Leiden, the Netherlands

   Mathematical Institute, Utrecht University, PO Box 80010, 3508 TA Utrecht, the Netherlands