Publication | Open Access
<i>SHARP</i>: a distributed GPU-based ptychographic solver
132
Citations
53
References
2016
Year
EngineeringGpu BenchmarkingAdvanced ImagingAdvanced Light SourceComputational IlluminationGpu ComputingReal-time ImagingComputational ImagingParallel ComputingRadiologyHealth SciencesParallel DetectorsLight Field ImagingOphthalmologyMedical ImagingComputer ScienceMedical Image ComputingGpu ClusterOptical ImagingComputational ScienceBiomedical ImagingParallel Programming
Ever brighter light sources, fast parallel detectors and advances in phase retrieval methods have made ptychography a practical and popular imaging technique. Compared to previous techniques, ptychography provides superior robustness and resolution at the expense of more advanced and time-consuming data analysis. By taking advantage of massively parallel architectures, high-throughput processing can expedite this analysis and provide microscopists with immediate feedback. These advances allow real-time imaging at wavelength-limited resolution, coupled with a large field of view. This article describes a set of algorithmic and computational methodologies used at the Advanced Light Source and US Department of Energy light sources. These are packaged as a CUDA-based software environment named SHARP (http://camera.lbl.gov/sharp), aimed at providing state-of-the-art high-throughput ptychography reconstructions for the coming era of diffraction-limited light sources.
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