Vivarium Cluster Tools
Vivarium cluster tools is a python package that makes running vivarium simulations at scale on a Slurm cluster easy.
Supported Python versions: 3.11, 3.12, 3.13
You can install vivarium-cluster-tools from PyPI with pip:
pip install vivarium-cluster-toolsor build it from source by cloning the monorepo and installing this package:
git clone https://github.com/ihmeuw/vivarium-suite.git
cd vivarium-suite
pip install libs/cluster-toolsA simple example
If you have a vivarium model specification file defining a particular model, you can use that along side a branches file to launch a run of many simulations at once with variations in the input data, random seed, or with different parameter settings.
psimulate run /path/to/model_specification.yaml /path/to/branches_file.yamlThe simplest branches file defines a count of input data draws and random seeds to launch.
input_draw_count: 25
random_seed_count: 10This branches file defines a set of simulations for all combinations of 25 input draws and 10 random seeds and so would run, in total, 250 simulations.
You can also define a set of parameter variations to run your model over. Say your original model specification looked something like
plugins:
optional: ...
components:
vivarium.public_health:
population:
- BasePopulation()
disease.models:
- SIS('lower_respiratory_infections')
my_lri_intervention:
components:
- GiveKidsVaccines()
configuration:
population:
population_size: 1000
age_start: 0
age_end: 5
lri_vaccine:
coverage: 0.2
efficacy: 0.8Defining a simple model of lower respiratory infections and a vaccine intervention. You could then write a branches file that varied over both input data draws and random seeds, but also over different levels of coverage and efficacy for the vaccine. That file would look like
input_draw_count: 25
random_seed_count: 10
branches:
- lri_vaccine:
coverage: [0.0, 0.2, 0.4, 0.8, 1.0]
efficacy: [0.4, 0.6, 0.8]The branches file would overwrite your original lri_vaccine configuration with each combination of coverage and efficacy in the branches file and launch a simulation. More, it would run each coverage-efficacy pair in the branches for each combination of input draw and random seed to produce 25 * 10 * 5 * 3 = 3750 unique simulations.
Multi-step workflows with dagger
For pipelines that chain several steps together, dagger runs a multi-step Jobmon workflow defined in a YAML configuration file. Each step lists its command and compute resources:
workflow:
name: my_pipeline
project: proj_simscience
queue: all.q
output_directory: /path/to/output
steps:
- name: launch_sims
command: psimulate run /path/to/model_specification.yaml /path/to/branches_file.yaml
resources:
memory_gb: 4
runtime: "01:00:00"
- name: post_process
command: my_post_processing_script /path/to/output
resources:
memory_gb: 8
runtime: "00:30:00"Launch the workflow with
dagger run -c /path/to/workflow.yamlIf a run fails partway through, resume it from its output directory, skipping steps that already completed, with
dagger restart /path/to/outputTo read about more of the available features and get a better understanding of how to correctly write your own branches files,
Check out the docs!
1 maintainer
Release files for vivarium-cluster-tools 4.7.1
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Source distribution (sdist)
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| vivarium_cluster_tools-4.7.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 284.3 kB
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