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Related Experiment Video

Updated: Feb 17, 2026

Author Spotlight: Enhancing Cryo-Electron Microscopy by Automated Data Collection and Analysis Techniques
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ICON-MIC: Implementing a CPU/MIC Collaboration Parallel Framework for ICON on Tianhe-2 Supercomputer.

Zihao Wang1,2,3, Yu Chen1,2,3, Jingrong Zhang1,2

  • 11 High Performance Computer Research Center, Institute of Computing Technology , Chinese Academy of Sciences, Beijing, China .

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|November 30, 2017
PubMed
Summary
This summary is machine-generated.

Electron tomography (ET) reconstruction, ICON, is enhanced by ICON-MIC, a parallel technology on Xeon Phi cards. This accelerates the process for studying biological structures, overcoming computational bottlenecks.

Keywords:
ICONMIC accelerationTianhe-2 supercomputer.electron tomographyhybrid task allocation strategyparallel NUFFT

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Area of Science:

  • Biophysics
  • Computational Biology
  • Structural Biology

Background:

  • Electron tomography (ET) is crucial for 3D biological ultrastructure analysis.
  • Sub-nanometer resolution in ET enables studying macromolecular complex dynamics.
  • The 'missing wedge' artifact limits ET reconstruction quality.

Purpose of the Study:

  • To address the computational demands of the ICON algorithm for ET reconstruction.
  • To accelerate the ICON algorithm using parallel processing on Xeon Phi cards.
  • To improve the efficiency and applicability of ET for biological structure analysis.

Main Methods:

  • Implementation of ICON-MIC, a parallelized version of ICON on Xeon Phi cards.
  • Parallelization of matrix operations and nonuniform fast Fourier transform (NUFFT) calculations.
  • Development of a hybrid task allocation strategy for load balancing on supercomputers.

Main Results:

  • ICON-MIC achieves significant acceleration (up to 13.3x) compared to the CPU version.
  • The method demonstrates high accuracy in reconstructing biological specimens across various noise levels.
  • ICON-MIC shows good scalability and performance on the Tianhe-2 supercomputer.

Conclusions:

  • ICON-MIC effectively overcomes computational bottlenecks in ET reconstruction.
  • The parallelized approach enhances the practical application of ICON for biological ultrastructure studies.
  • This work provides a powerful and efficient tool for high-resolution 3D structural analysis in biology.