CK SDK installation¶

You can install the Collective Knowledge framework on most platforms using PIP as follows:

pip install ck

You can also install CK using a specific Python version (for example, Python 3.6 or for Python 2.7):

python3.6 -m pip install ck

or

python2.7 -m pip install ck

You may need to add flag “–user” to install the client in your user space:

pip install ck --user
python3.6 -m pip install ck --user

You should now be able to run CK using one of the following alternative commands:

ck

python3.6 -m ck

If the installation is successful, you will see some internal information about the CK installation and a Python version used:

CK version: 1.12.1

Python executable used by CK: /usr/bin/python

Python version used by CK: 2.7.12 (default, Oct  8 2019, 14:14:10)
   [GCC 5.4.0 20160609]

Path to the default repo: /home/fursin/fggwork/ck/ck/repo
Path to the local repo:   /home/fursin/CK/local
Path to CK repositories:  /home/fursin/CK

Documentation:        https://github.com/ctuning/ck/wiki
CK Google group:      https://bit.ly/ck-google-group
CK Slack channel:     https://cKnowledge.org/join-slack
Stable CK components: https://cKnowledge.io

Prerequisites¶

The CK framework requires minimal dependencies: Python 2.7+ or 3.x, PIP and Git.

Linux¶

You need to have the following packages installed (Ubuntu example):

sudo apt-get install python3 python3-pip git wget

MacOS¶

brew install python3 python3-pip git wget

Windows¶

Download and install Git from git-for-windows.github.io.
Download and install any Python from www.python.org/downloads/windows.

Android (Linux host)¶

These dependencies are needed to cross-compile for Android (tested on Ubuntu 18.04 including Docker and Windows 10 Subsystem for Linux).

 sudo apt update
 sudo apt install git wget libz-dev curl cmake
 sudo apt install gcc g++ autoconf autogen libtool
 sudo apt install android-sdk
 sudo apt install google-android-ndk-installer

Docker¶

We prepared several Docker images with the CK framework and AI/ML CK workflows at the cTuning Docker hub. Select the most relevant image and run it as follows:

docker run -p 3344:3344 -it {Docker image name from the above list} /bin/bash