A serial/parallel Monte Carlo and Machine Learning library for Python, MATLAB, Fortran, C++, and C, offering automated, user-friendly, high-performance, and scalable algorithms for scientific inference.
- auxil
- Published at
- Nov 10, 2024
- 308
- Stars
- 20,082
- Download
- Synced at
- 11m ago
Latest release
auxilNov 10, 2024, 05:33 AMPre-releaseDownloads slow? Switch the source anytime above
README
Project Overview
ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical density functions and Machine Learning algorithms for scientific inference, with design goals of automation, user-friendliness, accessibility, high-performance, and scalability.
Key Features
- Full automation: Automated Monte Carlo and Machine Learning simulations
- Interoperability: Core library supports C, C++, Fortran, MATLAB, and Python
- High-performance: Meticulously low-level implementation
- Parallelizability: OpenMP and MPI support with zero parallel-coding effort
- Zero-dependence: No external library dependencies
- Fully-deterministic reproducibility: Automatic restart functionality
Target Audience
- Data scientists and machine learning engineers
- Computational physics and statistical modeling researchers
- Developers who need high-performance Monte Carlo simulations
Quick Start
- Download prebuilt libraries from Releases
- Follow QUICKSTART.md
- Or build from source
Core Advantages
- Zero parallel-coding effort required
- Zero external dependencies
- Multi-language support
System Requirements
- OS: Cross-platform (Windows, Linux, macOS)
- Architectures: x86_64, arm64
Release history
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