From c9021072db08b834ef36496f4d8d65e440a43f05 Mon Sep 17 00:00:00 2001
From: AnthonyTsu1984 <115786031+AnthonyTsu1984@users.noreply.github.com>
Date: Thu, 12 Dec 2024 16:35:22 +0800
Subject: [PATCH] Update gpu_index.md
---
site/en/reference/gpu_index.md | 2 ++
1 file changed, 2 insertions(+)
diff --git a/site/en/reference/gpu_index.md b/site/en/reference/gpu_index.md
index 5a71b88ca..ba9cd1970 100644
--- a/site/en/reference/gpu_index.md
+++ b/site/en/reference/gpu_index.md
@@ -27,6 +27,7 @@ GPU_CAGRA is a graph-based index optimized for GPUs, Using inference-grade GPUs
| `graph_degree` | Affects search performance and recall by setting the graph's degree after pruning. A larger difference between these two degrees results in a longer build time. Its value must be smaller than the value of __intermediate_graph_degree__. | 64
|
| `build_algo` | Selects the graph generation algorithm before pruning. Possible values:IVF_PQ
: Offers higher quality but slower build time. NN_DESCENT
: Provides a quicker build with potentially lower recall. | IVF_PQ
|
| `cache_dataset_on_device` | Decides whether to cache the original dataset in GPU memory. Possible values:"true"
: Caches the original dataset to enhance recall by refining search results. "false"
: Does not cache the original dataset to save gpu memory. | "false"
|
+ | `adapt_for_cpu` | Decides whether to conduct searches solely on CPU and reserves GPU resources for other operations.
Setting this parameter to `true` requires the presence of the `ef` parameter carried in the search requests. | "false"
|
- Search parameters
@@ -36,6 +37,7 @@ GPU_CAGRA is a graph-based index optimized for GPUs, Using inference-grade GPUs
| `search_width` | Specifies the number of entry points into the CAGRA graph during the search. Increasing this value can enhance recall but may impact search performance(e.g. 1, 2, 4, 8, 16, 32). | Empty |
| `min_iterations` / `max_iterations` | Controls the search iteration process. By default, they are set to `0`, and CAGRA automatically determines the number of iterations based on `itopk_size` and `search_width`. Adjusting these values manually can help balance performance and accuracy. | `0` |
| `team_size` | Specifies the number of CUDA threads used for calculating metric distance on the GPU. Common values are a power of 2 up to 32 (e.g. 2, 4, 8, 16, 32). It has a minor impact on search performance. The default value is `0`, where Milvus automatically selects the `team_size` based on the vector dimension. | `0` |
+ | `ef` | Specifies the query time/accuracy trade-off. A higher `ef` value leads to more accurate but slower search.
This parameter is mandatory if you set `adapt_for_cpu` to `true` when you build the index. | `[top_k, int_max]` |
* Limits on search