[QST] How to predict the memory required to build an index with CagraIndex using IVFPQ
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Description
What is your question?
I am trying to build a CagraIndex(intermediate graph using IVFPQ) with 10M 768D documents. Anytime I am trying to build the index I am getting OOM exceptions.
My Machine:
- g5.2xlarge
- CPU RAM: 32GB
- GPU memory: 24GB
- Using Faiss python bindings to build the index. I have validated that Faiss is using the Cuvs and not raft.
I would like to know how I can predict the machine size required to build the index?
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Research direction
Start by reproducing the CagraIndex build with the stated 10M 768D dataset, IVFPQ configuration, Faiss Python bindings, and g5.2xlarge memory limits. Trace the index-building memory requirements and document a reliable sizing method, with completion defined as guidance that explains or predicts the required CPU and GPU memory.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- search
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100