Collective Knowledge components for TensorFlow (code, data sets, models, packages, workflows):
CK repository with components and automation actions to enable portable workflows across diverse platforms including Linux, Windows, MacOS and Android. It includes software detection plugins and meta packages (code, data sets, models, scripts, etc) with the possibility of multiple versions to co-exist in a user or system environment.
CK automation actions to let users implement portable, customizable and reusable program workflows for reproducible, collaborative and multi-objective benchmarking, optimization and SW/HW co-design:
Collective Knowledge repository with actions to unify the access to different predictive analytics engines (scipy, R, DNN) from software, command line and web-services via CK JSON API:
Collective Knowledge crowd-tuning extension to let users crowdsource their experiments (using portable Collective Knowledge workflows) such as performance benchmarking, auto tuning and machine learning across diverse platforms with Linux, Windows, MacOS and Android provided by volunteers. Demo of DNN crowd-benchmarking and crowd-tuning:
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):
Collective Knowledge workflow for ARM's workload automation tool: an open framework for gathering and sharing knowledge about system design and optimization using real-world workloads.
The procedures and a workflow to prepare Student Cluster Competition submissions:
CM interface and automation recipes to analyze MLPerf Inference, Tiny and Training results. The goal is to make it easier for the community to visualize, compare and reproduce MLPerf results and add derived metrics such as Performance/Watt or Performance/$
Integration of the Lift project with the Collective Knowledge (CK) framework
ARM's workloads in the universal Collective Knowledge Format with JSON API and JSON meta information to power Workload Automation Framework
Extra resources in the Collective Knowledge Format for ARM's Workload Automation Framework:
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