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kferjaoui
5489b68285
PixelHistogramCUDA_<input>_<storage> for uint16, float32 and float64 frames and the six storage types of PixelHistogram, behind an aare.PixelHistogramCUDA() factory. Frames are never converted: a wrong dtype raises TypeError, so a registered buffer is always the one copied. The GIL is released during GPU work. - C++: fill_histogram() and submit_batch() take const views, so read-only arrays (np.memmap mode="r") work; register_output_buffer() pins the destination of values(out). - Python: register_input_buffer()/register_output_buffer() keep their array alive; values(out=...) writes into a given array. With a pinned out, reading back a 640 MB histogram takes 28 ms instead of 230 ms. - Tests in test_PixelHistogramCUDA.py; PixelHistogramCUDA.ipynb compares CPU and GPU on 100k Moench frames (identical, ~13x faster on the GPU).