Search Results for "high performance computing"

...Integrate natively with existing code and data from legacy, low-level or high-performance libraries and applications. The Cython language is a superset of the Python language that additionally supports calling C functions and declaring C types on variables and class attributes.

...Just apply one of the Numba decorators to your Python function, and Numba does the rest. Numba is designed to be used with NumPy arrays and functions. Numba generates specialized code for different array data types and layouts to optimize performance. Special decorators can create universal functions that broadcast over NumPy arrays just like NumPy functions do. Numba also works great with Jupyter notebooks for interactive computing, and with distributed execution frameworks, like Dask and Spark.

https://github.com/jplevyak/pyc Pyc is a python compiler intended for high performance computing and programming-in-the-large. It uses the IFA library to statically analyze python programs, catch potential errors and generate efficient code.