PERF: Update Autoscoper to include PSO optimization #69
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Refactor the Particle Swarm Optimization (PSO) implementation by introducing a
specialized Particle data structure alongside a particle collection.
This structure allows us to efficiently manage and track computed Normalized
Cross-Correlation (NCC) values for each particle. As a result, we now evaluate
each particle only once per iteration, as opposed to between 2 and 5 times in
the worst-case scenario.
This optimization has led to a remarkable reduction in per-frame execution time
on a typical workstation using the OpenCL back-end, dropping it from the range
of 9 to 18 seconds to a much-improved 3 to 6 seconds.
List of changes:
$ git shortlog 73eb359dc..4bdedd802 --no-merges
Anthony Lombardi (1):
PERF: Introduce particle data structure for PSO
Co-authored-by: Anthony Lombardi <[email protected]>
NicerNewerCar
approved these changes
Nov 7, 2023
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Refactor the Particle Swarm Optimization (PSO) implementation by introducing a specialized Particle data structure alongside a particle collection. This structure allows us to efficiently manage and track computed Normalized Cross-Correlation (NCC) values for each particle. As a result, we now evaluate each particle only once per iteration, as opposed to between 2 and 5 times in the worst-case scenario.
This optimization has led to a remarkable reduction in per-frame execution time on a typical workstation using the OpenCL back-end, dropping it from the range of 9 to 18 seconds to a much-improved 3 to 6 seconds.
List of changes: