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[Licence| Download | New Version Template] afbt_v1_0.tar.gz(264527 Kbytes)
Manuscript Title: Massively parallel data processing for quantitative total flow imaging with optical coherence microscopy and tomography
Authors: Marcin Sylwestrzak, Daniel Szlag, Paul Marchand, Ashwin S. Kumar, Theo Lasser
Program title: CudaOCMproc
Catalogue identifier: AFBT_v1_0
Distribution format: tar.gz
Journal reference: Comput. Phys. Commun. 217(2017)128
Programming language: CUDA/C, MATLAB.
Computer: Intel x64 CPU, GPU supporting CUDA technology.
Operating system: 64-bit Windows 7 Professional.
Has the code been vectorised or parallelized?: Yes, CPU code has been vectorized in MATLAB, CUDA code has been parallelized.
RAM: Dependent on users parameters, typically between several gigabytes and several tens of gigabytes
Keywords: GPU data processing, CUDA, Optical coherence tomography, Flow diagnostics, Three-dimensional microscopy.
PACS: 42.30.Wb, 42.25.Kb, 87.85.Ng.
Classification: 6.5, 18.

Nature of problem:
Speed up of data processing in optical coherence microscopy

Solution method:
Utilization of GPU for massively parallel data processing

Additional comments:
Compiled DLL library with source code and documentation, example of utilization (MATLAB script with raw data)

Running time:
1,8 s for one B-scan (140 x faster in comparison to the CPU data processing time)