hgdl

API for Distributed HPC Function Optimization

https://github.com/lbl-camera/hgdl

Science Score: 64.0%

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
  • Academic publication links
    Links to: sciencedirect.com, zenodo.org
  • Committers with academic emails
    3 of 8 committers (37.5%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.3%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

API for Distributed HPC Function Optimization

Basic Info
Statistics
  • Stars: 6
  • Watchers: 2
  • Forks: 2
  • Open Issues: 0
  • Releases: 19
Created over 4 years ago · Last pushed 8 months ago
Metadata Files
Readme License Citation Authors

README.md

HGDL

PyPI Documentation Status HGDL CI Codecov PyPI - License DOI

HGDL is an API for HPC distributed constrained function optimization. At the core, the algorithm uses local and global optimization and bump-function-based deflation to provide a growing list of unique optima of a differentiable function. This tackles the common problem of non-uniquness of optimization problems, especially in machine learning.

Usage

The following demonstrates a simple usage of the HGDL API.

```python import numpy as np from hgdl.hgdl import HGDL as hgdl from hgdl.support_functions import * import dask.distributed as distributed

bounds = np.array([[-500,500],[-500,500]])

dask_client = distributed.Client("10.0.0.184:8786")

a = hgdl(schwefel, schwefelgradient, bounds, globaloptimizer = "genetic", localoptimizer = "dNewton", #put in local optimzers from scipy.optimize.minimize numberofoptima = 30000, numepochs = 100)

x0 = np.random.uniform(low = bounds[:, 0], high = bounds[:,1],size = (20,2)) a.optimize(x0 = x0)

the thread is now released, but the work continues in the background

a.get_latest() ##prints the current result whenever queried

a.kill_client() ##stops the execution and returns the result ```

Credits

Main Developers: Marcus Noack (MarcusNoack@lbl.gov) and David Perryman. Several people from across the DOE national labs have given insights that led to the code in its current form. See AUTHORS for more details on that. HGDL is based on the HGDN algorithm by Noack and Funke.

Owner

  • Name: CAMERA
  • Login: lbl-camera
  • Kind: organization

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Noack"
  given-names: "Marcus Michael"
- family-names: "Pandolfi"
  given-names: "Ronald J."
- family-names: "Perryman"
  given-names: "David"
- family-names: "Harinarayan"
  given-names: "Krishnan"
- family-names: "Zwart"
  given-names: "Petrus H."
title: "HGDL"
version: 2.3.0
doi: 
date-released: 2025-07-01

GitHub Events

Total
  • Release event: 4
  • Watch event: 1
  • Delete event: 1
  • Push event: 7
  • Pull request event: 1
  • Create event: 4
Last Year
  • Release event: 4
  • Watch event: 1
  • Delete event: 1
  • Push event: 7
  • Pull request event: 1
  • Create event: 4

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 382
  • Total Committers: 8
  • Avg Commits per committer: 47.75
  • Development Distribution Score (DDS): 0.442
Past Year
  • Commits: 22
  • Committers: 2
  • Avg Commits per committer: 11.0
  • Development Distribution Score (DDS): 0.409
Top Committers
Name Email Commits
Marcus Michael Noack M****k@l****v 213
Elliott Perryman e****n@v****t 68
Ronald Pandolfi r****i@g****m 41
Ian Humphrey i****y@g****m 35
Elliott Perryman d****2@l****v 22
Marcus Noack m****n@m****m 1
David Perryman e****t@y****n 1
David Perryman d****2@h****u 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 2
  • Total pull requests: 22
  • Average time to close issues: 14 days
  • Average time to close pull requests: 5 days
  • Total issue authors: 1
  • Total pull request authors: 3
  • Average comments per issue: 2.0
  • Average comments per pull request: 0.86
  • Merged pull requests: 21
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 8 days
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • rfung-uwm-edu (2)
Pull Request Authors
  • ronpandolfi (11)
  • ihumphrey (10)
  • MarcusMNoack (2)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 534 last-month
  • Total dependent packages: 2
  • Total dependent repositories: 2
  • Total versions: 55
  • Total maintainers: 2
pypi.org: hgdl

HGDL Optimization

  • Homepage: https://github.com/lbl-camera/hgdl
  • Documentation: https://hgdl.readthedocs.io/
  • License: *** License Agreement *** HGDL Copyright (c) 2020, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: (1) Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. (2) Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. (3) Neither the name of the University of California, Lawrence Berkeley National Laboratory, U.S. Dept. of Energy nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. You are under no obligation whatsoever to provide any bug fixes, patches, or upgrades to the features, functionality or performance of the source code ("Enhancements") to anyone; however, if you choose to make your Enhancements available either publicly, or directly to Lawrence Berkeley National Laboratory, without imposing a separate written license agreement for such Enhancements, then you hereby grant the following license: a non-exclusive, royalty-free perpetual license to install, use, modify, prepare derivative works, incorporate into other computer software, distribute, and sublicense such enhancements or derivative works thereof, in binary and source code form.
  • Latest release: 2.3.3
    published 8 months ago
  • Versions: 55
  • Dependent Packages: 2
  • Dependent Repositories: 2
  • Downloads: 534 Last month
Rankings
Dependent packages count: 3.2%
Average: 8.9%
Dependent repos count: 11.6%
Downloads: 12.1%
Last synced: 7 months ago

Dependencies

requirements.txt pypi
  • bokeh *
  • dask >=2021.6.2
  • distributed >=2021.6.2
  • loguru *
  • matplotlib *
  • nbformat *
  • numpy *
  • paramiko *
  • plotly *
  • scipy *
  • versioneer *
  • wheel *
.github/workflows/HGDL-CI.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • codecov/codecov-action v2 composite
  • fnkr/github-action-ghr v1 composite
  • pypa/gh-action-pypi-publish release/v1 composite