TL;DR
Carlo.jl is a Julia-based Monte Carlo framework that simplifies development, offers parallel execution, organized data management, and statistical analysis, targeting complex physics simulations.
Contribution
It introduces a minimalist, flexible Monte Carlo framework in Julia with parallelization and data handling features tailored for physics research.
Findings
Efficient MPI-parallel scheduling demonstrated.
Organized storage improves simulation reproducibility.
Benchmark results show competitive performance.
Abstract
Carlo is a Monte Carlo simulation framework written in Julia. It provides MPI-parallel scheduling, organized storage of input, checkpoint, and output files, as well as statistical postprocessing. With a minimalist design, it aims to aid the development of high-quality Monte Carlo codes, especially for demanding applications in condensed matter and statistical physics. This hands-on user guide shows how to implement a simple code with Carlo and provides benchmarks to show its efficacy.
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