cTuning & MLCommons Collective Knowledge Challenges

[ Back ]

Add more models and hardware backends to the universal C++ implementation of MLPerf inference benchmarks from MLCommons

Open date: 2023 Jul 4

Closing date: 2023 Aug 17

Collective Knowledge Contributor award: Yes

Challenge

Add more models and hardware backends to the universal C++ implementation of MLPerf inference benchmarks) being developed by the MLCommons Task Force on Automation and Reproducibility.

Read this documentation to run reference implementations of MLPerf inference benchmarks using the CM automation language and use them as a base for your developments.

Check this ACM REP'23 keynote to learn more about our open-source project and long-term vision.

Prizes

All contributors will receive an official MLCommons Collective Knowledge contributor award (see this example).
The top contributors will receive cash prizes from MLCommons organizations and cKnowledge.org.

Organizers

Results

All accepted results will be publicly available in the CM format with derived metrics in this MLCommons repository, in MLCommons Collective Knowledge explorer and at official MLCommons website.

Self link