Fast data preprocessing with Graphics Processing Units for inverse problem solving in light-scattering measurements

- Non-paraxial ray tracing was used to correct aberrations of light-scattering data.
- Numerical aberration correction allows wide-angle measurements with simple lenses.
- GPU processing allows speeding up the calculations by 400.
- All subroutines were made available on GitHub repository.
- Fast data processing makes on-line, real-time particle characterisation feasible.

Utilising Compute Unified Device Architecture (CUDA) platform for Graphics Processing Units (GPUs) enables significant reduction of computation time at a moderate cost, by means of parallel computing. In the paper [Jakubczyk et al., Opto-Electron. Rev., 2016] we reported using GPU for Mie scattering inverse problem solving (up to 800-fold speed-up). Here we report the development of two subroutines utilising GPU at data preprocessing stages for the inversion procedure: (i) A subroutine, based on ray tracing, for finding spherical aberration correction function. (ii) A subroutine performing the conversion of an image to a 1D distribution of light intensity versus azimuth angle (i.e. scattering diagram), fed from a movie-reading CPU subroutine running in parallel. All subroutines are incorporated in PikeReader application, which we make available on GitHub repository. PikeReader returns a sequence of intensity distributions versus a common azimuth angle vector, corresponding to the recorded movie. We obtained an overall ∼400-fold speed-up of calculations at data preprocessing stages using CUDA codes running on GPU in comparison to single thread Matlab-only code running on CPU.