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A collection of reusable and cross-platform automation recipes (CM scripts) with a human-friendly interface and minimal dependencies to make it easier to build, run, benchmark and optimize AI, ML and other applications and systems across diverse and continuously changing models, data sets, software and hardware (cloud/edge)

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Unified and cross-platform CM interface for DevOps, MLOps and MLPerf

License Python Version Powered by CM. Downloads

CM script automation features test MLPerf inference bert (deepsparse, tf, onnxruntime, pytorch) MLPerf inference MLCommons C++ ResNet50 MLPerf inference ABTF POC Test Test Compilation of QAIC Compute SDK (build LLVM from src) Test QAIC Software kit Compilation

Please see the docs site for understanding CM scripts better. The mlperf-branch of the cm4mlops repository contains updated CM scripts specifically for MLPerf Inference. For more information on using CM for MLPerf Inference, visit the MLPerf Inference Documentation site.

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License

Apache 2.0

CM concepts

Check our ACM REP'23 keynote.

Authors

Grigori Fursin and Arjun Suresh

Major script developers

Arjun Suresh, Anandhu S, Grigori Fursin

Funding

We thank cKnowledge.org, cTuning foundation and MLCommons for sponsoring this project!

Acknowledgments

We thank all volunteers, collaborators and contributors for their support, fruitful discussions, and useful feedback!

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A collection of reusable and cross-platform automation recipes (CM scripts) with a human-friendly interface and minimal dependencies to make it easier to build, run, benchmark and optimize AI, ML and other applications and systems across diverse and continuously changing models, data sets, software and hardware (cloud/edge)

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  • Python 73.8%
  • Shell 12.7%
  • C++ 7.5%
  • C 3.1%
  • Batchfile 2.1%
  • Dockerfile 0.5%
  • Other 0.3%