  ParaMonte (standing for Parallel Monte Carlo) is a serial and
MPI/Coarray-parallelized library of Monte Carlo routines for sampling
mathematical objective functions of arbitrary-dimensions, in particular, the
posterior distributions of Bayesian models in data science, Machine Learning,
and scientific inference. The ParaMonte library has been developed with the
design goal of unifying the **automation**, **accessibility**,
**high-performance**, **scalability**, and **reproducibility** of Monte Carlo
simulations. The current implementation of the library includes **ParaDRAM**, a
**Para**llel **D**elyaed-**R**ejection **A**daptive **M**etropolis Markov Chain
Monte Carlo sampler, accessible from a wide range of programming languages
including C, C++, Fortran, with a unified Application Programming Interface and
simulation environment across all supported programming languages. The
ParaMonte library is MIT-licensed and is permanently located and maintained at
[https://github.com/cdslaborg/paramonte](https://github.com/cdslaborg/paramonte).
