Table of Contents
FAISS can search 100 million vectors in 5 milliseconds. It can also take 5 seconds. The difference is performance tuning. A FAISS performance tuning specialist knows the knobs to turn - and which ones to leave alone.
Key Tuning Parameters
A specialist understands:
- ✦ nprobe (for IVF indexes) - more probes = higher recall, lower speed
- ✦ efSearch (for HNSW) - exploration factor, similar trade-off
- ✦ nlist (number of IVF cells) - more cells = faster search but lower recall
- ✦ quantization (PQ, SQ, OPQ) - memory vs accuracy trade-offs
- ✦ batch size for GPU processing
GPU vs CPU Optimization
Best For
GPU:
High throughput, batch queries
CPU:
Low latency, single queries
Memory Limit
GPU:
VRAM (24-80GB per GPU)
CPU:
RAM (hundreds of GB)
Index Types
GPU:
Flat, IVF (strongly optimized)
CPU:
All types including HNSW
Cost
GPU:
Higher (GPU instances)
CPU:
Lower (CPU instances)
GPU for batch processing, CPU for real-time single queries. A specialist knows which fits your use case.
What to Measure
A performance specialist tracks:
- ✦ Recall@k (accuracy)
- ✦ Queries per second (throughput)
- ✦ P50/P95/P99 latency
- ✦ Memory usage
- ✦ Index build time
Typical Optimization Workflow
- ✦ Establish baseline metrics
- ✦ Benchmark multiple index configurations
- ✦ Measure recall degradation
- ✦ Optimize memory footprint
- ✦ Validate production traffic performance
Interview Questions
Increase nprobe (for IVF) or efSearch (for HNSW). Trade-off: latency will increase. Estimate new latency based on scaling factors.
Add product quantization (PQ). Use OPQ for better accuracy. May need to adjust nlist or train on more data.
Evidence of Real Expertise
- ✦ Published benchmark reports
- ✦ Experience with 10M+ vectors
- ✦ Knowledge of GPU memory optimization
- ✦ Recall and latency tuning experience
- ✦ Production incident troubleshooting history
Find a Tuning Expert
Performance tuning separates toy FAISS demos from production systems. Offline Pixel pre-vets FAISS specialists who have optimized indexes at scale. Raise a request, talk to candidates, fund the project, and approve payment when you're satisfied.
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