diff --git a/docs/source/raft_ann_benchmarks.md b/docs/source/raft_ann_benchmarks.md index 32be9f15c7..72a164c34f 100644 --- a/docs/source/raft_ann_benchmarks.md +++ b/docs/source/raft_ann_benchmarks.md @@ -4,28 +4,46 @@ This project provides a benchmark program for various ANN search implementations ## Table of Contents -- [RAFT ANN Benchmarks](#raft-ann-benchmarks) - - [Table of Contents](#table-of-contents) - - [Installing the benchmarks](#installing-the-benchmarks) - - [Conda](#conda) - - [Docker](#docker) - - [How to run the benchmarks](#how-to-run-the-benchmarks) - - [Step 1: Prepare Dataset](#step-1-prepare-dataset) - - [Step 2: Build and Search Index](#step-2-build-and-search-index) - - [Step 3: Data Export](#step-3-data-export) - - [Step 4: Plot Results](#step-4-plot-results) - - [Running the benchmarks](#running-the-benchmarks) - - [End to end: small-scale benchmarks (\<1M to 10M)](#end-to-end-small-scale-benchmarks-1m-to-10m) - - [End to end: large-scale benchmarks (\>10M vectors)](#end-to-end-large-scale-benchmarks-10m-vectors) - - [Running with Docker containers](#running-with-docker-containers) - - [End-to-end run on GPU](#end-to-end-run-on-gpu) - - [End-to-end run on CPU](#end-to-end-run-on-cpu) - - [Manually run the scripts inside the container](#manually-run-the-scripts-inside-the-container) - - [Evaluating the results](#evaluating-the-results) - - [Creating and customizing dataset configurations](#creating-and-customizing-dataset-configurations) - - [Adding a new ANN algorithm](#adding-a-new-ann-algorithm) - - [Implementation and Configuration](#implementation-and-configuration) - - [Adding a CMake Target](#adding-a-cmake-target) +- [Installing the benchmarks](#installing-the-benchmarks) + - [Conda](#conda) + - [Docker](#docker) +- [How to run the benchmarks](#how-to-run-the-benchmarks) + - [Step 1: prepare dataset](#step-1-prepare-dataset) + - [Step 2: build and search index](#step-2-build-and-search-index) + - [Step 3: data export](#step-3-data-export) + - [Step 4: plot results](#step-4-plot-results) +- [Running the benchmarks](#running-the-benchmarks) + - [End to end: small-scale (<1M to 10M)](#end-to-end-small-scale-benchmarks-1m-to-10m) + - [End to end: large-scale (>10M)](#end-to-end-large-scale-benchmarks-10m-vectors) + - [Running with Docker containers](#running-with-docker-containers) + - [Evaluating the results](#evaluating-the-results) +- [Creating and customizing dataset configurations](#creating-and-customizing-dataset-configurations) +- [Adding a new ANN algorithm](#adding-a-new-ann-algorithm) +- [Parameter tuning guide](https://docs.rapids.ai/api/raft/nightly/ann_benchmarks_param_tuning/) +- [Wiki-all RAG/LLM Dataset](https://docs.rapids.ai/api/raft/nightly/wiki_all_dataset/) +## Installing the benchmarks# RAFT ANN Benchmarks + +This project provides a benchmark program for various ANN search implementations. It's especially suitable for comparing GPU implementations as well as comparing GPU against CPU. + +## Table of Contents + +- [Installing the benchmarks](#installing-the-benchmarks) + - [Conda](#conda) + - [Docker](#docker) +- [How to run the benchmarks](#how-to-run-the-benchmarks) + - [Step 1: prepare dataset](#step-1-prepare-dataset) + - [Step 2: build and search index](#step-2-build-and-search-index) + - [Step 3: data export](#step-3-data-export) + - [Step 4: plot results](#step-4-plot-results) +- [Running the benchmarks](#running-the-benchmarks) + - [End to end: small-scale (<1M to 10M)](#end-to-end-small-scale-benchmarks-1m-to-10m) + - [End to end: large-scale (>10M)](#end-to-end-large-scale-benchmarks-10m-vectors) + - [Running with Docker containers](#running-with-docker-containers) + - [Evaluating the results](#evaluating-the-results) +- [Creating and customizing dataset configurations](#creating-and-customizing-dataset-configurations) +- [Adding a new ANN algorithm](#adding-a-new-ann-algorithm) +- [Parameter tuning guide](https://docs.rapids.ai/api/raft/nightly/ann_benchmarks_param_tuning/) +- [Wiki-all RAG/LLM Dataset](https://docs.rapids.ai/api/raft/nightly/wiki_all_dataset/) ## Installing the benchmarks