From 6fd5af3605db1053afdfb224f70f409add1664c5 Mon Sep 17 00:00:00 2001 From: liliu-z <105927039+liliu-z@users.noreply.github.com> Date: Mon, 3 Mar 2025 14:48:00 +0800 Subject: [PATCH] fix: [2.5] Change CMake variable for switch to knowhere-cuvs (#40289) issue: #39883 pr: #40105 Signed-off-by: Mickael Ide Signed-off-by: Li Liu Co-authored-by: Micka --- .gitignore | 1 + README.md | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 041d808936..947f2cb373 100644 --- a/.gitignore +++ b/.gitignore @@ -29,6 +29,7 @@ docker-compose-devcontainer.yml.tmp # Docker generated cache file .docker/ +.docker-gpu/ **/_artifacts/** diff --git a/README.md b/README.md index 37f30a370f..b8795ed9c7 100644 --- a/README.md +++ b/README.md @@ -75,7 +75,7 @@ Milvus is designed to handle vector search at scale. Users can store vectors, wh **Support for Various Vector Index Types and Hardware Acceleration** - * Milvus separates the system and core vector search engine, allowing it to support all major vector index types that are optimized for different scenarios, including HNSW, IVF, FLAT (brute-force), SCANN, and DiskANN, with [quantization-based](https://milvus.io/docs/index.md?tab=floating#IVFPQ) variations and [mmap](https://milvus.io/docs/mmap.md). Milvus optimizes vector search for advanced features such as [metadata filtering](https://milvus.io/docs/scalar_index.md#Scalar-Index) and [range search](https://milvus.io/docs/single-vector-search.md#Range-search). Additionally, Milvus implements hardware acceleration to enhance vector search performance and supports GPU indexing, such as NVIDIA's [CAGRA](https://github.com/rapidsai/raft). + * Milvus separates the system and core vector search engine, allowing it to support all major vector index types that are optimized for different scenarios, including HNSW, IVF, FLAT (brute-force), SCANN, and DiskANN, with [quantization-based](https://milvus.io/docs/index.md?tab=floating#IVFPQ) variations and [mmap](https://milvus.io/docs/mmap.md). Milvus optimizes vector search for advanced features such as [metadata filtering](https://milvus.io/docs/scalar_index.md#Scalar-Index) and [range search](https://milvus.io/docs/single-vector-search.md#Range-search). Additionally, Milvus implements hardware acceleration to enhance vector search performance and supports GPU indexing, such as NVIDIA's [CAGRA](https://github.com/rapidsai/cuvs). **Flexible Multi-tenancy and Hot/Cold Storage**