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Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition
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Published on: March 19, 2021

Addressing the computational cost of large EIT solutions.

Alistair Boyle1, Andrea Borsic, Andy Adler

  • 1Systems and Computer Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada. boyle@sce.carleton.ca

Physiological Measurement
|April 26, 2012
PubMed
Summary
This summary is machine-generated.

Electrical impedance tomography (EIT) computation times can be reduced by optimizing sparse matrix solvers. This study developed a tool to identify efficient solver and hardware configurations for EIT problems.

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Area of Science:

  • Medical Imaging
  • Computational Science
  • Electrical Engineering

Background:

  • Electrical impedance tomography (EIT) reconstructs interior conductivity using electrical measurements.
  • EIT computations are numerically intensive, limiting exploration of complex problems.
  • Multicore processors offer potential speedups but require algorithmic adaptation.

Purpose of the Study:

  • To profile EIT software (EIDORS, NDRM) and identify computational bottlenecks.
  • To develop a tool for measuring sparse matrix solver performance.
  • To guide the selection of optimal solver and hardware for EIT.

Main Methods:

  • Profiling of EIDORS and NDRM software packages.
  • Development of the Meagre-Crowd sparse matrix solver performance measurement tool.
  • Benchmarking solvers across 2D and 3D problems with varying node densities.

Main Results:

  • Sparse matrix solvers constitute a significant portion of EIT computation time.
  • Distributed sparse solvers show advantages on multicore processors, especially with increasing node density.
  • Performance is dependent on the specific solver and hardware configuration.

Conclusions:

  • Optimizing sparse matrix solvers is crucial for reducing EIT computation time.
  • The Meagre-Crowd tool aids in selecting appropriate solvers and hardware for EIT.
  • Efficient computational strategies will enable more advanced EIT applications.