Replaces CPU-bound vector search libraries with a high-performance GPU graph implementation. It utilizes a novel graph-based approach to achieve state-of-the-art recall and latency on massive datasets.
Tech Stack
CudaAI, ML & Data
Why ggnn?
• State-of-the-art GPU performance
• High recall accuracy
• Efficient memory management
Limitations
• Requires NVIDIA GPU hardware
• Complex C++ build process
• Steep learning curve for tuning
2/27/2026
Last Update
27
Forks
1
Issues
Apache-2.0
License
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