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Meta project for setting up the LHCb stack

Multimodal and Multiclass Machine Learning for High Energy Physics

Higgs to diphoton nanoAOD framework

Tools and classes to control Lab equipment

CERN Docker image to be used from CI jobs to deploy in the different central CERN Web service platforms.

Triple Modular Redundancy Generator

Automates the programmatic execution of a number of benchmarks (HS06, SPEC CPU 2017, HEP-score, etc) Formerly known as cloud-benchmark-suite

LHCbDIRAC is the Extension from DIRAC for LHCb Experiment

Docker image to build docker image on shared runners. Enables the use of (privileged) shared runners for docker builds by not allowing users to run arbitrary commands (provided the shared runner does not allow entrypoint override)

Configuration for the LHCb software stacks.

The software release guide is: https://lbdevops.web.cern.ch/lbdevops/SoftwareReleaseGuide.html

The releases status can be seen at: https://lhcb-nightlies.web.cern.ch/release/lhcb-release/

Dockerfiles for images that contain ATLAS and ML components with atlas-sit/docker as a dependency

CMS SAM plugins

A NanoAOD to Analysis NTuple Framework, based on RDataFrame, C++ and Python

Demonstrates how to build a docker image and upload it to a docker registry using GitLab CI and a Dockerfile kept in a GitLab repository.

Steer the HEP workloads' runs, collect results, compute the HEPscore and generate the full report