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Multi-GPU, Multi-Node Algorithms for Acceleration of Image Reconstruction in 3D Electrical Capacitance Tomography in

Michał Majchrowicz1, Paweł Kapusta1, Lidia Jackowska-Strumiłło1

  • 1Institute of Applied Computer Science, Lodz University of Technology, Stefanowskiego 18/22, 90-537 Lodz, Poland.

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|April 15, 2020
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Summary
This summary is machine-generated.

A new parallel computing approach significantly speeds up 3D Electrical Capacitance Tomography (ECT) image reconstruction. This method utilizes multi-GPU, multi-node systems for faster industrial process monitoring.

Keywords:
distributed systemselectrical capacitance tomographyheterogeneus systemmulti-GPU computations

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Area of Science:

  • Engineering
  • Computer Science
  • Physics

Background:

  • Electrical Capacitance Tomography (ECT) is a valuable non-invasive technique for industrial process visualization.
  • Traditional 3D ECT image reconstruction involves computationally intensive processes and large datasets, leading to significant time consumption.

Purpose of the Study:

  • To propose and evaluate a novel parallel computing approach for accelerating 3D ECT image reconstruction.
  • To enhance the efficiency and speed of data processing in 3D ECT systems.

Main Methods:

  • Development of a distributed measurement system featuring a new parallel computing framework and an ECT-specific plugin.
  • Implementation of multi-GPU, multi-node algorithms within a heterogeneous distributed system architecture.
  • Performance evaluation using LBP and Landweber's reconstruction algorithms, focusing on data distribution and transmission.

Main Results:

  • The proposed framework, integrated with a new network communication layer, substantially reduced data transfer times.
  • Significant improvements in overall system efficiency were achieved through parallelized data processing.
  • The parallel approach demonstrated a marked acceleration in the complex computations required for 3D ECT image reconstruction.

Conclusions:

  • The developed parallel computing framework offers an effective solution for accelerating 3D ECT image reconstruction.
  • This advancement enables faster and more efficient industrial process monitoring using 3D ECT.
  • The multi-GPU, multi-node strategy is crucial for overcoming the computational challenges in high-resolution 3D ECT imaging.