Circumventing The Linker: Using SciPy's BLAS and LAPACK Within Cython

By Ian Henriksen. 2015

3 citations recorded by the source corpus.

BLAS, LAPACK, and other libraries like them have formed the underpinnings of much of the scientific stack in Python. Until now, the standard practice in many packages for using BLAS and LAPACK has been to link each Python extension directly against the libraries needed. Each module that calls these low-level libraries directly has had to link against them independently. The task of finding and linking properly against the correct libraries has, in the past, been a substantial obstacle in the development and distribution of Python

Subfields: Artificial Intelligence, Information Systems and Management, Numerical Methods & Scientific Computing

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In Artificial Intelligence

1. K. Jarrod Millman
2. Pearu Peterson
3. Matthew Brett
4. S. Van Der Walt
5. Johannes L. Schönberger
6. Juan Nunez-Iglesias
7. Yaroslav O. Halchenko
8. Ian Henriksen

In Information Systems and Management

1. Matthew Brett
2. K. Jarrod Millman

In Numerical Methods & Scientific Computing

1. J. Vanderplas
2. Matthew Newville
3. Ian Henriksen
4. Juan Nunez-Iglesias
5. Felix Lenders
6. K. Jarrod Millman
7. Tiziano Zito
8. Fabian Pedregosa

Citations in the corpus

• SciPy 1.0: fundamental algorithms for scientific computing in Python (2019, methodology): “Developers can also use the low-level Cython interfaces without linking against the wrapped libraries 77 .”
• SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python (2019, methodology): “Developers can also use the low-level Cython interfaces without linking against the wrapped libraries 77 .”