Wavelet computing improvements #4
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added 2 commits
June 5, 2023 16:32
This change was mainly about moving from storing wavelets as functions to functors. Now wavelets can have extra parameters. This introduced a challenge of making the CUDA kernel accept these functors so templates were used. A helper utility was also introduced on operator side. RunForName function translates wavelet names and runs the right DALI kernel.
Discrete wavelets have been discarded since we're currently focusing on continuous wavelet transform. Computation of wavelet input samples has been moved to a separate cuda kernel which should give a speedup when computing wavelets for multiple a and b parameters. Input wavelet samples, their scaled values and b coefficient are stored in shared memory instead of global memory which should speedup computation.
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