OMP4Py Documentation

A native Python implementation of OpenMP

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OMP4Py is a Python library that provides a native implementation of OpenMP, which is widely recognized as the standard programming model for exploiting multithreading parallelism in HPC. OMP4Py enables developers to express familiar OpenMP constructs directly in Python through the omp4py.omp() entry point, which serves as the unified interface to manage directives, decorators and module registrations across the entire system.

OMP4Py features a dual-runtime architecture, consisting of a pure Python runtime and a native C-based runtime generated using Cython. This design combines the flexibility and ease of use of Python with the performance benefits of native execution, enabling developers to write parallel code with the same level of control and efficiency as in C, C++, or Fortran.

Compared to the Numba-based PyOMP, OMP4Py offers greater flexibility, as it imposes no restrictions on using functions from non-Numba-optimized libraries or Python objects. Experimental results show that OMP4Py achieves good performance and scalability for both numerical and non-numerical tasks. Additionally, OMP4Py code can be combined with mpi4py to develop parallel applications that exploit both intra-node and inter-node parallelism.

The documentation is organized for two audiences:

  • Final users who want to install OMP4Py, write parallel Python programs, run examples, and understand the supported directives.

  • Developers who want to understand the architecture, modify or extend OMP4Py’s core capabilities, run tests, or build and publish this documentation.

Contents

Getting Started

Citing OMP4Py

If you use OMP4Py in academic work, please cite: