Skip to main content

A Python-based scientific workflow ensemble manager for running concurrent UQ simulations on high-performance computers.

Project description

Themis

LLNL's Themis is a Python-based scientific workflow ensemble manager for running concurrent UQ simulations on high-performance computers. Using a simple, non-intrusive interface to simulation models, it provides the following capabilities:

  • generating ensemble of simulations leveraging LC's HPC resources
  • analyzing ensemble of simulations output

Themis has been used for simulations in the domains of Inertial Confinement Fusion, National Ignition Facility experiments, climate, as well as other programs and projects.

The themis package manages the execution of simulations. Given a set of inputs (sample points) to run a simulation on, this package will execute them in parallel, monitor their progress, and collect the results. The themis package work with Python 2 and 3.

Installation

To get the latest public version:

pip install llnl-themis

To get the latest stable from a cloned repo, simply run:

pip install .

Alternatively, add the path to this repo to your PYTHONPATH environment variable or in your code with:

import sys
sys.path.append(path_to_themis_repo)

Documentation

The documentation can be built from the docs directory using:

make html

Read the Docs coming soon.

Contact Info

Themis maintainer can be reached at: domyancic1@llnl.gov

Contributing

Contributing to Themis is relatively easy. Just send us a pull request. When you send your request, make develop the destination branch on the Themis repository.

Your PR must pass Themis' unit tests and documentation tests, and must be PEP 8 compliant. We enforce these guidelines with our CI process. To run these tests locally, and for helpful tips on git, see our Contribution Guide.

Themis' develop branch has the latest contributions. Pull requests should target develop, and users who want the latest package versions, features, etc. can use develop.

Contributions should be submitted as a pull request pointing to the develop branch, and must pass Themis' CI process; to run the same checks locally, use:

pytest tests/

Releases

See our change log for more details.

Code of Conduct

Please note that Themis has a Code of Conduct. By participating in the Themis community, you agree to abide by its rules.

License

Themis is distributed under the terms of the MIT license. All new contributions must be made under the MIT license. See LICENSE and NOTICE for details.

LLNL-CODE-838977

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llnl_themis-1.2.0.tar.gz (69.3 kB view details)

Uploaded Source

Built Distribution

llnl_themis-1.2.0-py3-none-any.whl (81.9 kB view details)

Uploaded Python 3

File details

Details for the file llnl_themis-1.2.0.tar.gz.

File metadata

  • Download URL: llnl_themis-1.2.0.tar.gz
  • Upload date:
  • Size: 69.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.12

File hashes

Hashes for llnl_themis-1.2.0.tar.gz
Algorithm Hash digest
SHA256 cb416b98547f27e031f2cd463d780beea471ca21b18c83cd8edca1eeef7c663d
MD5 35bba25b64485c77843e975ce644b662
BLAKE2b-256 a14f2f697157b8c86baeeb691c0819a2dbd162f0af76addb62f8b2e407084d40

See more details on using hashes here.

File details

Details for the file llnl_themis-1.2.0-py3-none-any.whl.

File metadata

  • Download URL: llnl_themis-1.2.0-py3-none-any.whl
  • Upload date:
  • Size: 81.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.12

File hashes

Hashes for llnl_themis-1.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 d79e686f4b6d05d054d0cd235fcd6cc752462e9d04434f3c949a7d12829ad11a
MD5 61f79b839bcbb85b4e70fa4c4e0b2448
BLAKE2b-256 118928bd0d654d4cf18fa4288dbf80884241ffc364815426f605b7fa9652f9e7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page