Carlo

Monte Carlo framework that provides MPI parallelization, checkpointing and statistical postprocessing in an algorithm-agnostic way.

https://github.com/lukas-weber/carlo.jl

Science Score: 44.0%

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  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
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  • Scientific vocabulary similarity
    Low similarity (9.2%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Monte Carlo framework that provides MPI parallelization, checkpointing and statistical postprocessing in an algorithm-agnostic way.

Basic Info
  • Host: GitHub
  • Owner: lukas-weber
  • License: mit
  • Language: Julia
  • Default Branch: main
  • Homepage:
  • Size: 46 MB
Statistics
  • Stars: 41
  • Watchers: 2
  • Forks: 2
  • Open Issues: 3
  • Releases: 11
Created over 3 years ago · Last pushed 8 months ago
Metadata Files
Readme Changelog License Citation

README.md

Carlo.jl

Docs dev Docs stable CI codecov

Carlo is a framework for developing high-performance, distributed (quantum) Monte Carlo simultations. Its aim is to take care of model-independent tasks such as

  • autocorrelation and error analysis,
  • Monte-Carlo-aware MPI scheduling, and
  • checkpointing

while leaving all the flexibility of implementating Monte Carlo updates and estimators to you.

Getting started

To install the package, type

julia using Pkg; Pkg.add("Carlo")

The package itself does not include Monte Carlo algorithms. The quickest way to see how to implement one yourself is to check out the reference implementation for the Ising model. For a state-of-the-art Monte Carlo code, take a look at StochasticSeriesExpansion.jl.

Owner

  • Name: Lukas Weber
  • Login: lukas-weber
  • Kind: user
  • Company: Simons Foundation

Physics postdoc at the Center for Computational Quantum Physics.

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Weber"
  given-names: "Lukas"
  orcid: "https://orcid.org/0000-0003-4949-5529"
title: "Carlo.jl"
doi: 10.48550/arXiv.2408.03386
date-released: 2024-08-06
url: "https://github.com/lukas-weber/Carlo.jl"

GitHub Events

Total
  • Create event: 5
  • Commit comment event: 6
  • Release event: 3
  • Issues event: 12
  • Watch event: 15
  • Delete event: 2
  • Issue comment event: 14
  • Push event: 42
  • Pull request event: 1
Last Year
  • Create event: 5
  • Commit comment event: 6
  • Release event: 3
  • Issues event: 12
  • Watch event: 15
  • Delete event: 2
  • Issue comment event: 14
  • Push event: 42
  • Pull request event: 1

Issues and Pull Requests

Last synced: 12 months ago

All Time
  • Total issues: 21
  • Total pull requests: 1
  • Average time to close issues: about 2 months
  • Average time to close pull requests: about 7 hours
  • Total issue authors: 4
  • Total pull request authors: 1
  • Average comments per issue: 1.38
  • Average comments per pull request: 2.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 13
  • Pull requests: 1
  • Average time to close issues: 18 days
  • Average time to close pull requests: about 7 hours
  • Issue authors: 3
  • Pull request authors: 1
  • Average comments per issue: 1.54
  • Average comments per pull request: 2.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • lukas-weber (13)
  • hz-xiaxz (5)
  • rkr8 (2)
  • JuliaTagBot (1)
Pull Request Authors
  • hz-xiaxz (3)
Top Labels
Issue Labels
enhancement (3) good first issue (2)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • julia 25 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 10
juliahub.com: Carlo

Monte Carlo framework that provides MPI parallelization, checkpointing and statistical postprocessing in an algorithm-agnostic way.

  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 25 Total
Rankings
Dependent repos count: 10.1%
Average: 23.4%
Dependent packages count: 36.7%
Last synced: 7 months ago