Collective Knowledge (software)

Collective Knowledge (CK)

Developer(s)	cTuning foundation and dividiti
Initial release	2014 (2014)
Stable release	1.9.1 / April 30, 2017 (2017-04-30)
Written in	Python
Operating system	Linux, Mac OS X, Microsoft Windows
Type	Knowledge management, Artifact Evaluation, Artifact Sharing, Package management system, Scientific workflow system
License	BSD License 3-clause
Website	github.com/ctuning/ck, cknowledge.org, cknowledge.org/ai, cknowledge.org/repo

The Collective Knowledge project (or CK for short) is an open-source framework and repository to enable collaborative and reproducible experimentation (originally focusing on computer systems' research). CK is a small, portable and customizable infrastructure which allows researchers:

• share their artifacts as reusable Python components with unified JSON API, JSON meta information, and distributed UID via GitHub and similar services
• quickly prototype experimental workflows from shared components as LEGO(R) (such as multi-objective autotuning)
• automate, crowdsource and reproduce experiments
• unify predictive analytics (scikit-learn, R, DNN)
• enable interactive articles and graphs.

Notable usages

• ARM uses CK to accelerate computer engineering
• Several ACM-sponsored conferences use CK for artifact evaluation
• Imperial College (London) uses CK to automate and crowdsource compiler bug detection
• Researchers from the University of Cambridge used CK to help the community reproduce results of their publication in the International Symposium on Code Generation and Optimization (CGO'17) during Artifact Evaluation
• General Motors (USA) uses CK to crowd-benchmark Convolutional Neural Network optimizations
• Volunteers provide spare computational resources (mobile phones, HPC servers) to crowdsource optimization of realistic workloads (such as DNN), share optimization statistics in a public repository of knowledge, and enable self-optimizing and self-learning computer systems.

Portable Package manager

CK has an integrated cross-platform package manager with Python scripts, JSON API and JSON meta-description to automatically rebuild software environment on a user machine required to run a given shared research workflow (see documentation for more details).

Extensible AI API

CK provides a unified and extensible JSON API for multiple DNN frameworks including Caffe and TensorFlow while optimizing them across diverse hardware (mobile devices, HPC servers) and models.

Reproducibility of experiments

CK enables reproducibility of experimental results via community involvement similar to Wikipedia and Physics. Whenever a new workflow with all components is shared via GitHub, anyone can try it on a different machine, with different environment and using slightly different choices (compilers, libraries, data sets). Whenever an unexpected or wrong behavior is encountered, the community explains it, fixes components and shares them back as conceptually described in.

External links

• Development site: [1]
• Documentation: [2]
• Resources related to open science: [3]
• Public repository of optimization knowledge: [4]
• Example of CK-powered research projects (collaborative benchmarking and optimization of CNN across diverse hardware): [5]
• Demo of an interactive article: [6]
• International Workshop on Adaptive Self-tuning Computing System (ADAPT) uses CK to enable public reviewing of publications and artifacts via Reddit: [7]
• Android application to crowdsource experiments (such as program optimization) using mobile devices provided by volunteers via CK framework: [8]