2022 September: We have released MLCommons CM v1.0.1 -
the next generation of the MLCommons Collective Knowledge framework being developed
by the public workgroup.
We are very glad to see that more than 80% of all performance results and more than 95% of all power results
were automated by the MLCommons CK v2.6.1 in the latest MLPerf inference round thanks to submissions from Qualcomm, Krai, Dell, HPE and Lenovo!
The Collective Knowledge framework (CK)
helps to organize any software project as a database of reusable components
(algorithms, datasets, models, frameworks, scripts, experimental results, papers, etc)
with common automation actions and extensible meta descriptions
based on FAIR principles (findability, accessibility, interoperability and reusability).
The goal is to make it easier for researchers, practitioners and students to reproduce, compare
and build upon techniques from published papers shared in the common CK format,
adopt them in production and reuse best R&D practices.
See how the CK technology helps to automate benchmarking, optimization and design space exploration
of ML Systems and accelerate AI, ML and System innovation: journal article,
ACM tech talk,
and some real-world use cases
from MLPerf, General Motors, Arm, IBM, Amazon, Qualcomm, DELL, the Raspberry Pi foundation and ACM.
Presentations about CK (ACM, General Motors and FOSDEM)