NVIDIA cuVS is an open source library for GPU-accelerated vector search and data clustering that enables faster vector searches and index builds.
What is NVIDIA cuVS?
NVIDIA cuVS contains state-of-the-art implementations of several algorithms for running approximate and exact nearest neighbors, vector compression, and clustering on the GPU. It can be used directly or through the various databases and other libraries that have integrated it. The primary goal of NVIDIA cuVS is to simplify the use of GPUs for vector similarity search, preprocessing, and clustering.
What Is NVIDIA cuVS Production Branch 6?
The NVIDIA cuVS Production Branch, exclusively available with NVIDIA AI Enterprise, is a 12-month supported, API-stable branch that includes monthly fixes for high and critical software vulnerabilities. This branch provides a stable and secure environment for building your mission-critical AI applications. The NVIDIA cuVS production branch releases every six months.
Where is NVIDIA cuVS used?
These are common places where vector search appear:
Semantic Search
- Generative AI: RAG & Agentic AI
- Recommender systems
- Computer vision
- Image search
- Text search
- Audio search
- Molecular search
- Model Training: LLMs & Transformers
Data mining
- Clustering algorithms
- Visualization algorithms
- Sampling algorithms
- Class balancing
- Ensemble methods
- k-NN graph construction
Documentation
To get started with NVIDIA cuVS, please see the following documentation: https://docs.nvidia.com/cuvs/home