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

Monte Carlo framework that provides MPI parallelization, checkpointing and statistical postprocessing in an algorithm-agnostic way.
https://github.com/lukas-weber/carlo.jl

Last synced: about 1 month ago
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Monte Carlo framework that provides MPI parallelization, checkpointing and statistical postprocessing in an algorithm-agnostic way.

• Host: GitHub
• URL: https://github.com/lukas-weber/carlo.jl
• Owner: lukas-weber
• License: mit
• Created: 2022-10-26T20:47:43.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2024-04-12T21:18:19.000Z (9 months ago)
• Last Synced: 2024-04-14T15:23:28.803Z (9 months ago)
• Language: Julia
• Homepage:
• Size: 36.9 MB
• Stars: 10
• Watchers: 2
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# ![Carlo.jl](docs/header.svg)

[![Docs dev](https://img.shields.io/badge/docs-latest-blue.svg)](https://lukas.weber.science/Carlo.jl/dev/)

[![Docs stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://lukas.weber.science/Carlo.jl/stable/)

[![CI](https://github.com/lukas-weber/Carlo.jl/workflows/CI/badge.svg)](https://github.com/lukas-weber/Carlo.jl/actions)

[![codecov](https://codecov.io/gh/lukas-weber/Carlo.jl/branch/main/graph/badge.svg?token=AI8CPOGKXF)](https://codecov.io/gh/lukas-weber/Carlo.jl)

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](https://github.com/lukas-weber/Ising.jl) model.

For a state-of-the-art Monte Carlo code, take a look at [StochasticSeriesExpansion.jl](https://github.com/lukas-weber/StochasticSeriesExpansion.jl).