https://github.com/madsjulia/robustpmap.jl
Robust pmap calls for efficient parallelization and high-performance computing
Science Score: 46.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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✓Academic publication links
Links to: scholar.google -
✓Committers with academic emails
1 of 3 committers (33.3%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (16.2%) to scientific vocabulary
Keywords
Repository
Robust pmap calls for efficient parallelization and high-performance computing
Basic Info
- Host: GitHub
- Owner: madsjulia
- License: gpl-3.0
- Language: Julia
- Default Branch: master
- Homepage: http://mads.gitlab.io
- Size: 54.7 KB
Statistics
- Stars: 2
- Watchers: 7
- Forks: 3
- Open Issues: 0
- Releases: 8
Topics
Metadata Files
README.md
RobustPmap
Robust paralleization using pmap calls with checks for the type of returned values. RobustPmap is a module of MADS.
MADS
MADS (Model Analysis & Decision Support) is an integrated open-source high-performance computational (HPC) framework in Julia. MADS can execute a wide range of data- and model-based analyses:
- Sensitivity Analysis
- Parameter Estimation
- Model Inversion and Calibration
- Uncertainty Quantification
- Model Selection and Model Averaging
- Model Reduction and Surrogate Modeling
- Machine Learning and Blind Source Separation
- Risk Assessment
- Decision Analysis and Support
MADS has been tested to perform HPC simulations on a wide-range of multi-processor clusters and parallel environments (Moab, Slurm, etc.). MADS utilizes adaptive rules and techniques which allows the analyses to be performed with a minimum user input. The code provides a series of alternative algorithms to execute each type of data- and model-based analysis.
Documentation
All the available MADS modules and functions are described at madsjulia.github.io
Installation
julia
Pkg.add("Mads")
Installation behind a firewall
Julia uses git for package management.
To install Julia packages behind a firewall, add the following lines in the .gitconfig file in your home directory:
git
[url "https://"]
insteadOf = git://
or execute:
bash
git config --global url."https://".insteadOf git://
Set proxies:
bash
export ftp_proxy=http://proxyout.<your_site>:8080
export rsync_proxy=http://proxyout.<your_site>:8080
export http_proxy=http://proxyout.<your_site>:8080
export https_proxy=http://proxyout.<your_site>:8080
export no_proxy=.<your_site>
For example, if you are doing this at LANL, you will need to execute the following lines in your bash command-line environment:
bash
export ftp_proxy=http://proxyout.lanl.gov:8080
export rsync_proxy=http://proxyout.lanl.gov:8080
export http_proxy=http://proxyout.lanl.gov:8080
export https_proxy=http://proxyout.lanl.gov:8080
export no_proxy=.lanl.gov
MADS examples
In Julia REPL, do the following commands:
julia
import Mads
To explore getting-started instructions, execute:
julia
Mads.help()
There are various examples located in the examples directory of the Mads repository.
For example, execute
julia
include(Mads.madsdir * "/../examples/contamination/contamination.jl")
to perform various example analyses related to groundwater contaminant transport, or execute
julia
include(Mads.madsdir * "/../examples/bigdt/bigdt.jl")
to perform Bayesian Information Gap Decision Theory (BIG-DT) analysis.
Developers
Projects:
Publications, Presentations
Owner
- Name: MADS: Model Analysis & Decision Support
- Login: madsjulia
- Kind: organization
- Email: velimir.vesselinov@gmail.com
- Location: USA
- Website: https://madsjulia.github.io
- Repositories: 21
- Profile: https://github.com/madsjulia
High-performance computational framework for data analytics, model diagnostics, machine learning & decision support
GitHub Events
Total
- Create event: 2
- Commit comment event: 4
- Release event: 2
- Issue comment event: 2
- Push event: 3
- Pull request event: 1
Last Year
- Create event: 2
- Commit comment event: 4
- Release event: 2
- Issue comment event: 2
- Push event: 3
- Pull request event: 1
Committers
Last synced: 8 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| monty | v****v@g****m | 63 |
| Daniel O'Malley | o****d@l****v | 7 |
| Tony Kelman | t****y@k****t | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 1
- Total pull requests: 3
- Average time to close issues: less than a minute
- Average time to close pull requests: over 1 year
- Total issue authors: 1
- Total pull request authors: 2
- Average comments per issue: 27.0
- Average comments per pull request: 0.33
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- JuliaTagBot (1)
Pull Request Authors
- tkelman (2)
- JuliaTagBot (2)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- julia 9 total
- Total dependent packages: 4
- Total dependent repositories: 17
- Total versions: 10
juliahub.com: RobustPmap
Robust pmap calls for efficient parallelization and high-performance computing
- Homepage: http://mads.gitlab.io
- Documentation: https://docs.juliahub.com/General/RobustPmap/stable/
- License: GPL-3.0
-
Latest release: 1.2.0
published over 1 year ago
Rankings
Dependencies
- julia-actions/setup-julia latest composite
- JuliaRegistries/TagBot v1 composite
- actions/checkout v2 composite