Collective Knowledge (CK) and Common Metadata eXchange (CMX): community-driven projects to learn how to run AI, ML and other emerging workloads in a more efficient and cost-effective way across diverse models, datasets, software and hardware using MLPerf automations, CK playground and open reproducibility and optimization challenges
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/$
A collection of portable, reusable and cross-platform automation recipes (CM scripts) to make it easier to build and benchmark AI systems across diverse models, data sets, software and hardware
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