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Quick start

The following sections describe how to use the HPC MultiBench tool from the command line.

Installation

To install the tool, clone and navigate to the repository, then use poetry to create a virtual environment as follows:

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git clone --recurse-submodules -j8 https://github.com/EdmundGoodman/hpc-multibench
cd hpc-multibench
poetry install --without docs,test,dev

Interactively reviewing sample results

Using the parallelism test plan in the hpccg-rs-kudu-results submodule as an example, we can interactively view the data as follows:

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poetry run hpc-multibench \
    -y generated_results/hpccg-rs-kudu-results/_test_plans/parallelism.yaml \
    -o generated_results/hpccg-rs-kudu-results/ \
    interactive

This will open a terminal-user interface allowing interactive visualisation of results. This is rendered inside the terminal, and as such does not require X-forwarding to be set up to present data and plot graphs.

We can see the required -y flag being used to select the YAML file for the test plan, and the option -o flag to point to the directory containing the sample data. The interactive subcommand then runs the program in interactice mode.

Dispatching runs

On a system with Slurm installed, runs can be dispatched as follows:

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poetry run hpc-multibench \
    -y generated_results/hpccg-rs-kudu-results/_test_plans/parallelism.yaml \
    record

Since the -o flag is not specified here, it will default to writing out the files to a directory called results/ at the root of the repository.

Reviewing runs non-interactively

Run results can also be viewed non-interactively as follows:

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poetry run hpc-multibench \
    -y generated_results/hpccg-rs-kudu-results/_test_plans/parallelism.yaml \
    -o generated_results/hpccg-rs-kudu-results/ \
    report

This will open a sequence of matplotlib windows and write out any export data as specified within the YAML file.