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Currently in ScalarQuantizer, ScalarQuantizer.fromVectorsAutoInterval() will issue 4 calls (per to scratch-batch, basically len(vector)/20) Selector.select() and ScalarQuantizer.fromVectors() will issue 2 calls. All of these 4/2 calls use the same vectors, just asking for different k values. If we use a multi-select algorithm, instead of separate select algorithms, we can speed up these calls, especially ScalarQuantizer.fromVectorsAutoInterval() which is repeating a lot of logic.
The size of the list to select from is practically 20*vector_dimensions, so this greater speed ups will be observed with larger dimensionality. (Or if ScalarQuantizer.SCRATCH_SIZE is ever increased)
The text was updated successfully, but these errors were encountered:
Description
Currently in
ScalarQuantizer
,ScalarQuantizer.fromVectorsAutoInterval()
will issue 4 calls (per to scratch-batch, basicallylen(vector)/20
)Selector.select()
andScalarQuantizer.fromVectors()
will issue 2 calls. All of these 4/2 calls use the same vectors, just asking for differentk
values. If we use amulti-select
algorithm, instead of separateselect
algorithms, we can speed up these calls, especiallyScalarQuantizer.fromVectorsAutoInterval()
which is repeating a lot of logic.The size of the list to select from is practically
20*vector_dimensions
, so this greater speed ups will be observed with larger dimensionality. (Or ifScalarQuantizer.SCRATCH_SIZE
is ever increased)The text was updated successfully, but these errors were encountered: