Web Reference: The main goal of OMP4py is to bring the familiar parallelization paradigm of OpenMP to Python, allowing Python developers to write parallel code with the same level of control and flexibility as in C, C++, or Fortran. We recently reported on our work [1] to add explicit parallel multithreading to Python. This system maps the most popular in-terface for multithreading in HPC (OpenMP [2]) onto Python. We used this with Numba and a version of LLVM that includes interfaces to OpenMP. We ran all computations on an an Intel(R) Xeon(R) E5-2699 v3 CPU CPU with 18 cores running at 2.30 GHz. For the multi-threaded programs with OpenMP we forced the threads to map onto specific cores with one thread per core using the following pair of environment variables:
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