Collective Knowledge workflow for Caffe to automate installation across diverse platforms and to collaboratively evaluate and optimize Caffe-based workloads across diverse hardware, software and data sets (compilers, libraries, tools, models, inputs):

• UpdatedNov 6, 2019
• CMake

Collective Knowledge extension with unified and customizable benchmarks (with extensible JSON meta information) to be easily integrated with customizable and portable Collective Knowledge workflows. You can easily compile and run these benchmarks using different compilers, environments, hardware and OS (Linux, MacOS, Windows, Android). More info:

• UpdatedSep 21, 2021
• C

Integration of Caffe2 to Collective Knowledge workflow framework to provide unified CK JSON API for AI (customized builds across diverse libraries and hardware, unified AI API, collaborative experiments, performance optimization and model/data set tuning):

• UpdatedJul 10, 2021
• Python

Standalone, thin and portable server to let users participate in experiment crowdsourcing using Windows devices via Collective Knowledge Framework:

• UpdatedApr 29, 2017
• C

Crowdsourcing video experiments (such as collaborative benchmarking and optimization of DNN algorithms) using Collective Knowledge Framework across diverse Android devices provided by volunteers. Results are continuously aggregated in the open repository:

• UpdatedDec 20, 2018
• Java

Cohortz & Kohortz - Collaboration Portal

• UpdatedApr 21, 2017

Public results in the Collective Knowledge Format (JSON meta data) from collaborative optimization of computer systems. See live repository:

• UpdatedJul 10, 2021
• E

Extra resources in the Collective Knowledge Format for ARM's Workload Automation Framework:

• UpdatedDec 20, 2022
• Python