https://github.com/cdslaborg/paramonte
ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.
https://github.com/cdslaborg/paramonte
adaptive-learning bayesian-inference bayesian-statistics c cpp fortran machine-learning machine-learning-algorithms machine-learning-library markov-chain matlab mcmc monte-carlo monte-carlo-simulations mpi numerical-integration openmp python sampling
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ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.
- Host: GitHub
- URL: https://github.com/cdslaborg/paramonte
- Owner: cdslaborg
- License: other
- Created: 2020-02-04T23:16:39.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2024-05-20T06:02:02.000Z (12 months ago)
- Last Synced: 2024-05-20T07:53:01.008Z (12 months ago)
- Topics: adaptive-learning, bayesian-inference, bayesian-statistics, c, cpp, fortran, machine-learning, machine-learning-algorithms, machine-learning-library, markov-chain, matlab, mcmc, monte-carlo, monte-carlo-simulations, mpi, numerical-integration, openmp, python, sampling
- Language: Fortran
- Homepage: https://www.cdslab.org/paramonte
- Size: 52.6 MB
- Stars: 243
- Watchers: 11
- Forks: 31
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGES.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.MIT
Awesome Lists containing this project
README
Overview |
Installation |
Dependencies |
Parallelism |
Examples |
Acknowledgments |
License |
Authors
ParaMonte: Parallel Monte Carlo and Machine Learning
====================================================
ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical density functions of arbitrary dimensions and
Machine Learning (ML) algorithms for scientific inference, with the design goal of unifying **automation** (of simulations and tasks),
**user-friendliness** (of algorithms), **accessibility** (from any platform or programming environment),
**high-performance** (at runtime), and **scalability** (across many parallel processors).
For more information on the installation, usage, and examples, visit https://www.cdslab.org/paramonte
ParaMonte Design Goals
======================
ParaMonte has been developed while bearing the following design goals in mind:
- **Full automation** of Monte Carlo and Machine Learning simulations as much as possible to ensure user-friendliness
of the library and minimal time investment requirements for building, running, and post-processing simulation models.
- **Interoperability** of the core library with as many programming languages as currently possible,
including C, C++, Fortran, MATLAB, and Python, with ongoing efforts to support other popular programming languages.
- **High-Performance** meticulously-low-level library implementation to ensure the fastest-possible inferences.
- **Parallelizability** of all simulations via shared-memory OpenMP threads and two-sided and one-sided
MPI/Coarray distributed communications while requiring zero-parallel-coding efforts by the user.
- **Zero-dependence** on external libraries to ensure hassle-free ParaMonte library builds and ParaMonte simulation runs.
- **Fully-deterministic reproducibility** and automatically-enabled restart functionality
for all simulations with arbitrary digits of precision as requested by the user.
- **Comprehensive reporting and post-processing** of simulations and ML tasks, as well as their automatic storage in
external files to ensure the simulation results will be understandable and reproducible at any time in the foreseeable future.
Quick Start
===========
+ Follow the quick start instructions in this [QUICKSTART.md](https://github.com/cdslaborg/paramonte/blob/main/QUICKSTART.md) file.
+ For programming languages other than C, C++, Fortran, see the quick start section of the README.md file in the corresponding
language's source subfolder in the [src folder](https://github.com/cdslaborg/paramonte/src) in the root directory of the ParaMonte repository.
Installation
============
The prebuilt, ready-to-use libraries are available on
[the release page of the ParaMonte library on GitHub](https://github.com/cdslaborg/paramonte/releases).
Each prebuilt ParaMonte library automatically ships with a full-fledged set of example codes and build scripts.
Alternatively, you can build the library from the source
in the project's [GitHub repository](https://github.com/cdslaborg/paramonte).
The ParaMonte library installation/build process is fully automated for all supported programming languages.
Currently, the following compiler suites are supported **for builds from source**,
| Compiler Suite | Windows (amd64) | Linux (amd64) | macOS (amd64) | macOS (arm64) |
|----------------------------------:|:---------------:|:-------------:|:-------------:|:-------------:|
| GNU Compiler Collection >= 10.3 | ✅ | ✅ | ✅ | ✅ |
| Intel OneAPI >= 2021.8.0 | ✅ | ✅ | ✅ | ❌ |
with the following essential build systems,
| Dependency | Windows (amd64) | Linux (amd64) | macOS (amd64) | macOS (arm64) |
|----------------------------------:|:---------------:|:-------------:|:-------------:|:-------------:|
| CMake >= 3.21 | ✅ | ✅ | ✅ | ✅ |
+ Read the [`install.md` installation instruction notes](install.md)
to learn about the library's optional build configurations.
+ For a quickstart in the programming language of your choice,
visit the [ParaMonte library homepage](https://www.cdslab.org/paramonte).
Dependencies
============
Aside from an optional MPI runtime library for MPI-parallel simulations,
the ParaMonte library core has **zero dependency** on external third-party libraries or packages.
Parallelism
===========
The ParaMonte library relies on three independent parallelism paradigms for parallel applications:
1. The Coarray parallelism (only available for select routines in the Fortran programming language).
2. The Message Passing Interface (MPI) standard for inter-processor distributed parallelism.
+ On **Windows** and **Linux** operating systems, we highly recommend downloading and
installing the [Intel MPI runtime libraries](https://software.intel.com/en-us/mpi-library),
which is available to the public free of charge.
The [ParaMonte auxil prerelease](https://github.com/cdslaborg/paramonte/releases/tag/auxil)
exclusively contains the optional Intel MPI runtime libraries for users' convenience.
The Intel MPI requires the ParaMonte library to be (or have been prebuilt) using the Intel compilers.
+ On **macOS** (where Intel MPI is unavailable) and **Linux** operating systems, users can install
either [Open-MPI](https://www.open-mpi.org/) or [MPICH](https://www.mpich.org/) MPI runtime
libraries depending on the prebuilt version of the ParaMonte library that you have
downloaded or the configuration with which you intend to build the library.
**Optional Dependency Compatibility**
| Dependency | Windows (amd64) | Linux (amd64) | macOS (amd64) | macOS (arm64) |
|----------------------------------:|:---------------:|:-------------:|:-------------:|:-------------:|
| Intel MPI (IMPI) >= 2021.8 | ✅ | ✅ | ✅ | ❌ |
| MPICH MPI (MMPI) >= 3 | ❌ | ✅ | ✅ | ✅ |
| OpenMPI (OMPI) >= 4 | ❌ | ✅ | ✅ | ✅ |
Read the [`install.md` installation instruction notes](install.md) to
learn more about the library's optional parallel build configurations.
For more information, visit [https://www.cdslab.org/paramonte/](https://www.cdslab.org/paramonte/).
Example Usage Instructions
==========================
+ The best way to get started with example usage is to build the language-specific library examples.
The library example build and run scripts are automatically generated for each ParaMonte build and
are automatically stored in the output installation directory of the build.
+ For complete, organized, up-to-date instructions, visit: [cdslab.org/pm](https://www.cdslab.org/paramonte)
+ For a quick look into *language-specific* README.md instructions, visit:
+ **C**: [https://github.com/cdslaborg/paramonte/tree/main/src/c](https://github.com/cdslaborg/paramonte/tree/main/src/c)
+ **C++**: [https://github.com/cdslaborg/paramonte/tree/main/src/cpp](https://github.com/cdslaborg/paramonte/tree/main/src/cpp)
+ **Fortran**: [https://github.com/cdslaborg/paramonte/tree/main/src/fortran](https://github.com/cdslaborg/paramonte/tree/main/src/fortran)
+ **MATLAB**: [https://github.com/cdslaborg/paramonte/tree/main/src/matlab](https://github.com/cdslaborg/paramonte/tree/main/src/matlab)
+ The ParaMonte library for Python is currently undergoing internal testing before their impending release.
For now, the previous versions (1) of the ParaMonte Python libraries can be downloaded and used from the previous
library major release on [GitHub Release Page](https://github.com/cdslaborg/paramonte/releases/tag/v1.5.1).
Citing ParaMonte
================
The ParaMonte library is an honor-ware and its currency is acknowledgment and citations.
If you use ParaMonte or any ideas from this software, please acknowledge it by citing the ParaMonte library's
main publications as listed in [ACKNOWLEDGMENT.md](https://github.com/cdslaborg/paramonte/blob/main/ACKNOWLEDGMENT.md).
Visit [the ParaMonte library homepage](https://www.cdslab.org/paramonte/generic/latest/overview/preface/#how-to-acknowledge-the-use-of-the-paramonte-library-in-your-work)
to access the PDF version of these files free of charge.
License
=======
The majority of the ParaMonte library routines are distributed under the permissive
[MIT License](LICENSE.md) plus acknowledgments that are detailed in [LICENSE.md](./LICENSE.md).
However, there are occasionally modernized and extended routines from external projects, particularly within the ParaMonte Fortran library.
These routines may have a license that does not fully overlap with the default ParaMonte library license [LICENSE.md](./LICENSE.md).
In such cases, the documentation and source code of the specific routine explicitly list the original license information.
This is free software, so help us keep it freely available to the public by acknowledging the usage and contributing to it.
If you have questions or concerns about the license, please get in touch with the project's lead ([email protected]).
Authors and Contributors
========================
+ [Amir Shahmoradi](https://www.cdslab.org/people/#amir-shahmoradi)
+ Astrophysicist/bioinformatician by training,
+ Ph.D. in computational physics/bioinformatics, The University of Texas at Austin,
+ Currently a faculty member of the Data Science and Physics programs at UT Arlington,
+ Contact: [[email protected]](mailto:"[email protected]")
+ [Fatemeh Bagheri](https://www.linkedin.com/in/fbagheri)
+ PhD in Astronomy,
+ PhD in Space Physics,
+ Deep philosophical thinker,
+ Currently at NASA Goddard Space Flight Center,
+ Contact: [[email protected]](mailto:"[email protected]")
+ [Joshua Osborne](https://www.cdslab.org/people/#joshua-alexander-osborne)
+ Physicist / computational data scientist by training,
+ Currently a Physics PhD candidate at UT Arlington,
+ Contact: [[email protected]](mailto:"[email protected]")
Contributing to ParaMonte
=========================
Please read the generic contribution guidelines listed in [CONTRIBUTING.md](./CONTRIBUTING.md).
**For more information**, visit [cdslab.org/pm](https://www.cdslab.org/paramonte) or contact Amir Shahmoradi: [[email protected]](mailto:"[email protected]")