MOVING OLD FORTRAN TO PYTHON WHILE MAINTAINING FORTRAN-LEVEL PERFORMANCE

Авторы

  • Yodgarov Samad Jo'rayevich ( Nizomiy nomidagi TDPU ) Umumiy matematika kafedrasi dotsenti, matematika fanlari nomzodi
  • Ro'ziqulov Sa'dulla Egamnazarovich ( Nizomiy nomidagi TDPU ) magistrant
  • Nasirov Batiy-xan Sultanovich ( Nizomiy nomidagi TDPU ) 5110100-Matematika va informatika bakalavriatining ikkinchi mutaxassi
  • Zairov Ravshan Baxtiyarovich ( Nizomiy nomidagi TDPU ) 5110100-Matematika va informatika bakalavriatining ikkinchi mutaxassi
  • Tatarina Valentina Aleksandrovna ( Nizomiy nomidagi TDPU ) 5110100-Matematika va informatika bakalavriatining ikkinchi mutaxassi
  • Ten Viktoriya Anatolevna ( Nizomiy nomidagi TDPU ) 5110100-Matematika va informatika bakalavriatining ikkinchi mutaxassi

Ключевые слова:

Application migration, gradual typing, interop- erability, just-in-time compilation, legacy code, software main- tenance, transpilation.

Аннотация

 

We propose a method of accelerating Python code by just-in-time compilation leveraging type hints mechanism introduced in Python 3.5. In our approach performance-critical kernels are expected to be written as if Python was a strictly typed language, however without the need to extend Python syntax. This approach can be applied to any Python applica- tion, however we focus on a special case when legacy Fortran applications are automatically translated into Python for easier maintenance. We developed a framework implementing two- way transpilation and achieved performance equivalent to that of Python manually translated to Fortran, and better than using other currently available JIT alternatives (up to 5x times faster than Numba in some experiments).

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Опубликован

2023-01-29