# Cuda

> Browse 4 items tagged with Cuda.

## Items

- [NVIDIA cuVS](https://vectordb.ever.works/items/nvidia-cuvs) — NVIDIA cuVS is a GPU-accelerated approximate nearest neighbor search library utilizing CUDA for high-performance CAGRA, HNSW, IVF-PQ indexes on billion-scale datasets. Supports batch queries for high-throughput operations, ideal for large-scale similarity search and real-time recommendations. Delivers up to 12x faster index building and 8x lower query latency compared to CPU-only implementations like Milvus.
- [cuVS](https://vectordb.ever.works/items/cuvs) — NVIDIA RAPIDS cuVS is a GPU-accelerated library for vector search and clustering with CUDA-optimized HNSW, IVF, CAGRA, and PQ implementations. Supports batch queries for high QPS, suited for large-scale similarity search in GenAI apps. Achieves up to 12x faster indexing and lower latency vs CPU-only alternatives like FAISS CPU.
- [PilotANN](https://vectordb.ever.works/items/pilotann) — Memory-bounded GPU-accelerated framework for graph-based ANN vector search using CUDA and LibTorch, optimized for large-scale workloads beyond GPU memory. Features batch processing for high efficiency; outperforms CPU-only ANN in speed for similarity search in vector databases.
- [RUMMY](https://vectordb.ever.works/items/rummy-gpu-vector-search) — GPU-accelerated vector query processing system using CUDA to handle datasets larger than GPU memory via reordered pipelining and cluster-based retrofitting. Supports batch queries with up to 135x speedup over traditional GPU methods and 23x vs CPU-only for large-scale similarity search and MIPS.

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