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BP: Fachverband Biologische Physik
BP 13: Posters: Imaging and Superresolution Optical Microscopy
BP 13.12: Poster
Montag, 16. März 2015, 17:30–19:30, Poster A
Parallelizing super-resolution optical fluctuation imaging (SOFI) — •Bartosz Kohnke1, Stephan Kramer1, Johannes Hagemann2, and Suzunosuke Nagaoka3 — 1Max-Planck-Institut f. biophysikalische Chemie, Am Faßberg 11, 37077 Göttingen — 2Institut F. Röntgenphysik, Universität Göttingen, Friedrich-Hund-Platz 1, 37077 Göttingen — 3Institut f. Informatik, Universität Göttingen, Goldschmidtstraße 7, 37077 Göttingen
SOFI algorithms [1] are based on the observation that a higher order statistical analysis of a time series may be utilized for generating super-resolved images by computing per-pixel auto-cumulants, e.g. of a fluorescence signal. As the effectiveness of SOFI has been accepted in the microscopy community, our focus is on the speedup due to a careful design of a parallel implementation on current multi- and many-core compute architectures. In addition, we present robust, single-pass algorithms suitable for an adaptive computation of the final SOFI image in case of large-scale data analysis where the usual two-pass algorithms are unfeasible. We compare the performance on different parallelization frameworks, in particular Intel’s threading building blocks, Qt’s QThreads, CUDA and OpenCL. For the CUDA implementation we use our SciPAL library [2,3].
[1] Dertinger et al., PNAS Vol. 106, No. 52, pp. 22287 (2009)
[2] SciPAL: Expression Templates and Composition Closure Objects for High Performance Computational Physics with CUDA and OpenMP, S. C. Kramer and J. Hagemann, ACM TOPC (to appear).
[3] https://code.google.com/p/scipal/