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Not everyone has GPUs and in some cases hashing time may not be a bottleneck, so it would be nice to have a mode that does not require CUDA and firends.
AFAIK to have such option, alongside with high-performance GPU one would require small changes in hasher.py to have an option of using something like https://github.com/ekzhu/datasketch instead of libMHCUDA.
The text was updated successfully, but these errors were encountered:
@bzz it seems to be out of the research scope. We are going to hash the same data hundreds and thousands of times to find the best metaparameters. So this is a Gemini feature to me.
Not everyone has GPUs and in some cases hashing time may not be a bottleneck, so it would be nice to have a mode that does not require CUDA and firends.
AFAIK to have such option, alongside with high-performance GPU one would require small changes in hasher.py to have an option of using something like https://github.com/ekzhu/datasketch instead of libMHCUDA.
The text was updated successfully, but these errors were encountered: