48 Star 187 Fork 77

GVPopenEuler / A-Tune

Create your Gitee Account
Explore and code with more than 5 million developers,Free private repositories !:)
Sign up
Clone or download
Cancel
Notice: Creating folder will generate an empty file .keep, because not support in Git
Loading...
README.md

English | 简体中文

Introduction to A-Tune

A-Tune is an OS tuning engine based on AI. A-Tune uses AI technologies to enable the OS to understand services, simplify IT system optimization, and maximize optimal application performance.

I. A-Tune Installation

Supported OS: openEuler 1.0 or later

Method 1 (applicable to common users): Use the default A-Tune of openEuler.

yum install -y atune

For openEuler 20.09 or later, atune-engine is needed

yum install -y atune-engine

Method 2 (applicable to developers): Use the source code of the local repository for installation.

1. Install dependent system software packages.

yum install -y golang-bin python3 perf sysstat hwloc-gui

2. Install Python dependent packages.

yum install -y python3-dict2xml python3-flask-restful python3-pandas python3-scikit-optimize python3-xgboost python3-pyyaml

Or

pip3 install dict2xml Flask-RESTful pandas scikit-optimize xgboost scikit-learn pyyaml

3. Download the source code.

git clone https://gitee.com/openeuler/A-Tune.git

4. Compile.

cd A-Tune
make models
make

5. Install.

make collector-install
make install

II. Quick Guide

1. Manage the atuned service.

Load and start the atuned service.

systemctl daemon-reload
systemctl start atuned
systemctl start atune-engine

Check the atuned service status.

systemctl status atuned

2. Run the atune-adm command.

The list command.

This command is used to list the supported workload types, profiles, and the values of Active.

Format:

atune-adm list

Example:

atune-adm list

The analysis command.

This command is used to collect real-time statistics from the system to identify and automatically optimize workload types.

Format:

atune-adm analysis [OPTIONS] [APP_NAME]

Example 1: Use the default model for classification and identification.

atune-adm analysis

Example 2: Use the user-defined training model for recognition.

atune-adm analysis –model ./model/new-model.m

Example 3: Specify the current system application as MySQL, which is for reference only.

atune-adm analysis mysql

For details about other commands, see the atune-adm help information or A-Tune User Guide.

III. Web UI

A-Tune-UI is a web project base on A-Tune. Please check A-Tune-UI README for details.

IV. How to contribute

We welcome new contributors to participate in the project. And we are happy to provide guidance for new contributors. You need to sign CLA before contribution.

Mail list

Any question or discussion please contact A-Tune.

Routine Meeting

Holding SIG Meeting at 10:00-12:00 AM on Friday every two weeks. You can apply topic by A-Tune mail list.

About

A-Tune is an OS tuning engine based on AI. spread retract
Go and 5 more languages
MulanPSL-2.0
Cancel

Releases (3)

All

Gitee Metrics

Contributors

All

Activities

load more
can not load any more
Go
1
https://git.oschina.net/openeuler/A-Tune.git
git@git.oschina.net:openeuler/A-Tune.git
openeuler
A-Tune
A-Tune
master

Search