Using the madgraph4gpu benchmarking (BMK) containers

The HEP-benchmarks project provides docker and singularity containers that fully encapsulate typical software workloads of the LHC experiments. A test container based on madgraph4gpu, using the standalone tests with cudacpp matrix elements, has recently been added:

• https://gitlab.cern.ch/hep-benchmarks/hep-workloads/-/tree/master/mg5amc/madgraph4gpu-2022

The current version of the container is v0.6, it is available from the following locations:

• docker: https://gitlab.cern.ch/hep-benchmarks/hep-workloads/container_registry/14469
• singularity: https://registry.cern.ch/harbor/projects/892/repositories/mg5amc-madgraph4gpu-2022-bmk/artifacts-tab

The following is an example, where the singularity cache dir and tmp dir are also redirected:

  export SINGULARITY_TMPDIR=/scratch/SINGULARITY_TMPDIR
  export SINGULARITY_CACHEDIR=/scratch/SINGULARITY_CACHEDIR
  singularity run -B /scratch/TMP_RESULTS:/results oras://registry.cern.ch/hep-workloads/mg5amc-madgraph4gpu-2022-bmk:v0.6 -h

The containers are configurable. Using -h will print out a list of options. These are still UNDER TEST: please report any issues to AndreaV. Both CPU and GPU tests are available.

• For CPU tests, you may use -c to change the number of simultaneous copies that run on your node as separate (single threaded) processes. You should typically use $(nproc) copies to fill the CPU, and you can also try overcommitting the node.
• For GPU tests, it is recommended that you use -c1 to have a single copy running. The GPU is able to also share amongst different CPU processes, but the overhead reduces the overall throughput.