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I have downloaded 1 billion vectors (subset) from the original SPACEV1B dataset hosted on the SPTAG repo . The groundtruth was computed manually.
I'm using a slightly modified version of the bench_gpu_1bn.py script file to run ANN on SPACEV1B.
The recall values reported are relatively low (around 0.3). the index used is : OPQ24_96,IVF262144,PQ24.
Tried experimenting higher PQ values like 38, 32 etc but no significant improvement.
From the big-ann-benchmarks competition baseline, the suggested index is : IVF1048576,SQ8. Planning to try this index next. The GPU benchmark scripts in FAISS repo don't seem to support this SQ index.
Platform
OS: Ubuntu 22.04.1 LTS
Faiss version: 1.7.4
Installed from: Conda
Faiss compilation options:
Running on:
CPU
GPU
Interface:
C++
Python
Reproduction instructions
The text was updated successfully, but these errors were encountered:
Space1B should not be too problematic, see tab2 in https://proceedings.mlr.press/v176/simhadri22a/simhadri22a.pdf
Support for SQ8 was added to Faiss after the GPU bench script. However, if you run on a single GPU the dataset may not fit in the GPU ram.
Summary
I have downloaded 1 billion vectors (subset) from the original SPACEV1B dataset hosted on the SPTAG repo . The groundtruth was computed manually.
I'm using a slightly modified version of the bench_gpu_1bn.py script file to run ANN on SPACEV1B.
The recall values reported are relatively low (around 0.3). the index used is : OPQ24_96,IVF262144,PQ24.
Tried experimenting higher PQ values like 38, 32 etc but no significant improvement.
From the big-ann-benchmarks competition baseline, the suggested index is : IVF1048576,SQ8. Planning to try this index next. The GPU benchmark scripts in FAISS repo don't seem to support this SQ index.
Platform
OS: Ubuntu 22.04.1 LTS
Faiss version: 1.7.4
Installed from: Conda
Faiss compilation options:
Running on:
Interface:
Reproduction instructions
The text was updated successfully, but these errors were encountered: