Science Score: 75.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 4 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
    8 of 9 committers (88.9%) from academic institutions
  • Institutional organization owner
    Organization llnl has institutional domain (software.llnl.gov)
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (18.4%) to scientific vocabulary

Keywords

exploratory-data-analysis heterogeneous-computing hpc performance performance-analysis python

Keywords from Contributors

comparative-analysis data-analytics graphs hierarchical-data radiuss trees
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
Statistics
  • Stars: 19
  • Watchers: 3
  • Forks: 9
  • Open Issues: 34
  • Releases: 9
Topics
exploratory-data-analysis heterogeneous-computing hpc performance performance-analysis python
Created over 3 years ago · Last pushed 6 months ago
Metadata Files
Readme Contributing License Citation

README.md

thicket Thicket

Build Status codecov.io Read the Docs Code Style: Black

Thicket

A Python-based toolkit for Exploratory Data Analysis (EDA) of parallel performance data that enables performance optimization and understanding of applications’ performance on supercomputers. It bridges the performance tool gap between being able to consider only a single instance of a simulation run (e.g., single platform, single measurement tool, or single scale) and finding actionable insights in multi-dimensional, multi-scale, multi-architecture, and multi-tool performance datasets. You can find detailed documentation, along with tutorials of Thicket in the ReadtheDocs.

Installation

To use thicket, install it with pip:

$ pip install llnl-thicket

Or, if you want to develop with this repo directly, run the install script from the root directory, which will build the package and add the cloned directory to your PYTHONPATH:

$ source install.sh

Contact Us

You can direct any feature requests or questions to the Lawrence Livermore National Lab's Thicket development team by emailing either Stephanie Brink (brink2@llnl.gov) or Olga Pearce (pearce8@llnl.gov).

Contributing

To contribute to Thicket, please open a pull request to the develop branch. Your pull request must pass Thicket's unit tests, and must be PEP 8 compliant. Please open issues for questions, feature requests, or bug reports.

Authors and citations

Many thanks to Thicket's contributors.

Thicket was created by Olga Pearce and Stephanie Brink.

To cite Thicket, please use the following citation:

  • Stephanie Brink, Michael McKinsey, David Boehme, Connor Scully-Allison, Ian Lumsden, Daryl Hawkins, Treece Burgess, Vanessa Lama, Jakob Lüttgau, Katherine E. Isaacs, Michela Taufer, and Olga Pearce. 2023. Thicket: Seeing the Performance Experiment Forest for the Individual Run Trees. In the 32nd International Symposium on High-Performance Parallel and Distributed Computing (HPDC'23), August 2023, Pages 281–293. doi.org/10.1145/3588195.3592989.

On GitHub, you can copy this citation in APA or BibTeX format via the "Cite this repository" button. Or, see CITATION.cff for the raw BibTeX.

License

Thicket is distributed under the terms of the MIT license.

All contributions must be made under the MIT license. Copyrights in the Thicket project are retained by contributors. No copyright assignment is required to contribute to Thicket.

See LICENSE and NOTICE for details.

SPDX-License-Identifier: MIT

LLNL-CODE-834749

Owner

  • Name: Lawrence Livermore National Laboratory
  • Login: LLNL
  • Kind: organization
  • Email: github-admin@llnl.gov
  • Location: Livermore, CA, USA

For over 70 years, the Lawrence Livermore National Laboratory has applied science and technology to make the world a safer place.

Citation (CITATION.cff)

cff-version: 1.2.0
title: Thicket
message: "If you use Thicket, please cite it as below."
repository-code: https://github.com/llnl/thicket
preferred-citation:
  type: conference-paper
  doi: 10.1145/3588195.3592989
  url: https://github.com/llnl/thicket
  authors:
  - family-names: Brink
    given-names: Stephanie
  - family-names: McKinsey
    given-names: Michael
  - family-names: Boehme
    given-names: David
  - family-names: Scully-Allison
    given-names: Connor
  - family-names: Lumsden
    given-names: Ian
  - family-names: Hawkins
    given-names: Daryl
  - family-names: Burgess
    given-names: Treece
  - family-names: Lama
    given-names: Vanessa
  - family-names: Luettgau
    given-names: Jakob
  - family-names: Isaacs
    given-names: Katherine E.
  - family-names: Taufer
    given-names: Michela
  - family-names: Pearce
    given-names: Olga
  title: "Thicket: Seeing the Performance Experiment Forest for the Individual Run Trees"
  conference:
    name: "International Symposium on High-Performance Parallel and Distributed Computing"
    city: "Orlando"
    region: "Florida"
    country: "USA"
    date-start: 2023-06-20
    date-end: 2023-06-23
  year: 2023
  notes: LLNL-CODE-834749
  publisher:
    name: ACM
    city: "New York"
    region: "New York"
    country: "USA"

GitHub Events

Total
  • Create event: 10
  • Release event: 5
  • Issues event: 14
  • Watch event: 6
  • Delete event: 6
  • Issue comment event: 37
  • Push event: 39
  • Pull request event: 66
  • Pull request review event: 45
  • Pull request review comment event: 24
Last Year
  • Create event: 10
  • Release event: 5
  • Issues event: 14
  • Watch event: 6
  • Delete event: 6
  • Issue comment event: 37
  • Push event: 39
  • Pull request event: 66
  • Pull request review event: 45
  • Pull request review comment event: 24

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 97
  • Total Committers: 9
  • Avg Commits per committer: 10.778
  • Development Distribution Score (DDS): 0.649
Top Committers
Name Email Commits
Stephanie Brink b****2@l****v 34
Michael Mckinsey n****y@l****v 26
Vanessa Lama l****1@l****v 8
Connor Scully-Allison c****n@n****u 7
Ian Lumsden l****n@g****m 6
Connor Scully-Allison s****1@l****v 5
Michael Richard Mckinsey m****y@c****v 4
Michael Richard Mckinsey m****y@c****v 4
Treece Burgess n****"@l****v 3
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 43
  • Total pull requests: 233
  • Average time to close issues: 2 months
  • Average time to close pull requests: about 1 month
  • Total issue authors: 6
  • Total pull request authors: 15
  • Average comments per issue: 0.53
  • Average comments per pull request: 0.52
  • Merged pull requests: 190
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 15
  • Pull requests: 56
  • Average time to close issues: about 2 months
  • Average time to close pull requests: about 1 month
  • Issue authors: 4
  • Pull request authors: 6
  • Average comments per issue: 0.13
  • Average comments per pull request: 0.59
  • Merged pull requests: 41
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • ilumsden (14)
  • michaelmckinsey1 (13)
  • slabasan (8)
  • Yejashi (5)
  • MichaelMcKinsey1 (2)
  • pearzt (1)
Pull Request Authors
  • michaelmckinsey1 (116)
  • slabasan (59)
  • ilumsden (34)
  • MichaelMcKinsey1 (29)
  • Yejashi (15)
  • Treece-Burgess (10)
  • vanessalama09 (8)
  • dyokelson (7)
  • AndyM1098 (6)
  • pearce8 (4)
  • Julius-Plehn (4)
  • cscully-allison (3)
  • draganaurosgrbic (2)
  • guspan-tanadi (2)
  • marcusritter1 (1)
Top Labels
Issue Labels
priority-normal (20) type-bug (15) area-thicket (9) type-feature (8) priority-high (5) area-deployment (5) area-stats (3) area-ci (3) area-tests (2) area-utils (2) area-extrap (2) type-internal-cleanup (2) area-visualization (1) area-docs (1) priority-urgent (1) type-release (1) area-external (1) status-work-in-progress (1)
Pull Request Labels
priority-normal (186) status-ready-for-review (161) type-feature (94) area-thicket (93) type-bug (73) area-docs (39) status-approved (29) area-stats (28) area-tests (26) type-release (24) type-internal-cleanup (21) status-ready-to-merge (21) priority-high (17) status-work-in-progress (16) area-visualization (13) area-ci (11) area-utils (10) area-deployment (9) area-external (9) area-query-lang (8) priority-urgent (7) area-extrap (4) status-revisions-needed (2) status-blocked (2) status-help-wanted (1)

Packages

  • Total packages: 3
  • Total downloads:
    • pypi 3,936 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 0
    (may contain duplicates)
  • Total versions: 23
  • Total maintainers: 1
proxy.golang.org: github.com/LLNL/thicket
  • Versions: 8
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.6%
Average: 5.8%
Dependent repos count: 5.9%
Last synced: 6 months ago
proxy.golang.org: github.com/llnl/thicket
  • Versions: 8
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.6%
Average: 5.8%
Dependent repos count: 5.9%
Last synced: 6 months ago
pypi.org: llnl-thicket

Toolkit for exploratory data analysis of ensemble performance data

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 3,936 Last month
Rankings
Dependent packages count: 6.6%
Forks count: 19.6%
Average: 21.1%
Stargazers count: 23.3%
Downloads: 25.3%
Dependent repos count: 30.6%
Maintainers (1)
Last synced: 6 months ago

Dependencies

.github/workflows/unit-tests.yaml actions
  • actions/checkout v2 composite
  • actions/setup-node v3 composite
  • actions/setup-python v2 composite
  • codecov/codecov-action d9f34f8cd5cb3b3eb79b3e4b5dae3a16df499a70 composite
.github/workflows/build_and_upload_wheels.yaml actions
  • actions/checkout v3 composite
  • actions/download-artifact v3 composite
  • actions/setup-python v2 composite
  • actions/upload-artifact v3 composite
  • pypa/gh-action-pypi-publish v1.5.0 composite
docs/environment.yml pypi