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A distributed ASTRA toolbox.

Willem Jan Palenstijn1, Jeroen Bédorf2, Jan Sijbers3

  • 1CWI, Amsterdam, The Netherlands.

Advanced Structural and Chemical Imaging
|December 27, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a distributed ASTRA toolbox extension, enabling iterative reconstruction algorithms for tomography to run on multi-GPU clusters. This overcomes computational limitations, making advanced imaging techniques more accessible for large datasets.

Keywords:
Distributed computationReconstructionTomography

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Area of Science:

  • Computational Imaging
  • Scientific Software Development
  • Tomographic Reconstruction

Background:

  • Iterative reconstruction algorithms offer advantages over backprojection but face computational challenges in large-scale tomography.
  • Developing efficient distributed algorithms for GPU clusters requires complex low-level programming.

Purpose of the Study:

  • To extend the ASTRA toolbox for distributed, multi-GPU, and multi-workstation processing.
  • To enable high-level scripting of distributed tomography algorithms for large datasets.

Main Methods:

  • Developed distributed implementations of forward projection, backprojection, and the SIRT algorithm within the ASTRA toolbox.
  • Integrated tools for creating custom distributed reconstruction algorithms.
  • Ensured seamless execution on GPU-enabled computing clusters (up to 32 GPUs).

Main Results:

  • The extended ASTRA toolbox allows high-level scripts to run distributed tomography algorithms on clusters.
  • Processing of large datasets using ASTRA is now feasible.
  • The approach supports portability between different tomography setups (e.g., synchrotron to laboratory).

Conclusions:

  • The ASTRA toolbox extension significantly reduces the complexity of distributed iterative reconstruction.
  • This advancement enhances the accessibility and scalability of advanced tomography for large-scale imaging facilities.