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Tuning the cache memory usage in tomographic reconstruction on standard computers with Advanced Vector eXtensions

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  • 1Dep. Informatica, Universidad de Almeria, 04120 Almeria, Spain.

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Cache blocking optimizes tomographic reconstruction performance by strategically reusing data in cache memory. This study provides data for tuning block sizes for faster 3D image reconstruction.

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Area of Science:

  • Scientific Computing
  • Image Reconstruction
  • High-Performance Computing

Background:

  • Cache blocking is crucial for optimizing data exchange with main memory in scientific computing.
  • Effective cache utilization is central to high-performance tomographic reconstruction using vector instructions.

Purpose of the Study:

  • To present data from a performance study of tomographic reconstruction.
  • To investigate the impact of varying cache block sizes on reconstruction speed.
  • To enable automatic, quasi-optimal tuning of cache block sizes.

Main Methods:

  • Dividing sinograms and volume slices into small, cache-fitting blocks.
  • Reorganizing code to maximize data reuse within cache levels.
  • Systematic variation of cache block sizes to assess performance.

Main Results:

  • Demonstrated the significant impact of cache block size on tomographic reconstruction performance.
  • Collected comprehensive data correlating block sizes with computational efficiency.
  • Established a basis for deriving expressions for automatic cache block size optimization.

Conclusions:

  • Cache blocking is a key technique for accelerating 3D tomographic reconstruction.
  • Understanding cache behavior allows for significant performance gains.
  • The presented data facilitates automated optimization of reconstruction parameters.