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Option to turn on parallel computation for CCG in numba #4305
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for more information, see https://pre-commit.ci
…e into parallel_correlograms
for more information, see https://pre-commit.ci
…e into parallel_correlograms
alejoe91
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Thanks @yger
I would remove the fast_mode args from the numpy implementation since it's not used.
Also, maybe worth setting fast_mode="auto" by default and enable it in case of many units/many spikes?
Co-authored-by: Alessio Buccino <alejoe9187@gmail.com>
Co-authored-by: Alessio Buccino <alejoe9187@gmail.com>
Co-authored-by: Alessio Buccino <alejoe9187@gmail.com>
Co-authored-by: Alessio Buccino <alejoe9187@gmail.com>
Co-authored-by: Alessio Buccino <alejoe9187@gmail.com>
Co-authored-by: Alessio Buccino <alejoe9187@gmail.com>
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I've made fast_mode "auto" by default, (can also be "never" or "always"). "auto" means that if there are more than 300 neurons and "numba", it is activated |
for more information, see https://pre-commit.ci
Maybe "off"/"on" instead of never/always? :) |
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done, let's go for on/off |
This PR adds the possibility to activate a fast_mode for the numba implementation. The mode will parallelize use prange(), but at the cost of some (rare) racing conditions that might possibily bring some numerical instabilities. Tested on 1000 units firing at few herz for 1000s, the error is less than one spike out of a million compared to the normal one