| Age | Commit message (Collapse) | Author | 
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context can be setup and torn down correctly around the test.
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calculation of the path to the CUDA source code in one place.
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only run specific tests.  Names currently include: ray, load, propagate, pdf, pdf_eval
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with create_cuda_context().
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of the event.
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speed from 3.3M -> 3.45!.
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the GPU, and run the DAQ multiple times on the same photons in a
likelihood calculation.
Propagating the same photons in a warp speeds up propagation by a
factor of 3 (and we could do this even better if we wanted), and this
improves the statistics in a likelihood evaluation quite a bit.
Running the DAQ multiple times is also an inexpensive way to improve
the quality of the PDF estimates.
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together before creating leaf nodes in the bounding volume hierarchy.
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current GPU class. get full path name for cuda source inclusion in get_cu_module() and get_cu_source() so that it works when called from outside the package directory.
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np.apply_along_axis(np.linalg.norm,...) is really slow!
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