On Apr 26, 6:14 am, Francois Bissey wrote: > Actually do we know what version of > ATLAS/BLAS/LAPACK is shipped with OSX?
I couldn't figure out how to check that... All I found are a few posts on macresearch.org, which I didn't find helpful four our problem, http://www.macresearch.org/tutorial-using-lapack-fortran-95#comment-15416 http://www.macresearch.org/lapack-multi-thread-issue http://www.macresearch.org/lapack-test and the following pages on Apple's developer site: http://developer.apple.com/library/mac/#featuredarticles/AccelerateFrameworkData/_index.html http://developer.apple.com/hardwaredrivers/ve/vector_libraries.html http://developer.apple.com/library/mac/#documentation/Darwin/Reference/ManPages/10.5/man7/LAPACK.7.html the second one having some warnings about C vs Fortran syntax for specifying arrays, but I'm not sure if this is any help, and the third one having the paragraphs below about BLAS and LAPACK. BLAS The Basic Linear Algebra Subroutines (BLAS) are high quality routines for performing basic vector and matrix operations. Level 1 BLAS consists of vector-vector operations, Level 2 BLAS consists of matrix-vector operations, and Level 3 BLAS have matrix-matrix operations. The efficiency, portability, and the wide adoption of the BLAS have made them commonplace in the development of high quality linear algebra software such as LAPACK and in other technologies requiring fast vector and matrix calculations. All the industry standard FORTRAN BLAS entry points and the standard C BLAS entry points are exported from the vecLib framework (the latter are commonly denoted the legacy C BLAS.) For more information refer to <http://www.netlib.org/blas/faq.html> LAPACK LAPACK provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. The associated matrix factorizations (LU, Cholesky, QR, SVD, Schur, generalized Schur) are also provided, as are related computations such as reordering of the Schur factorizations and estimating condition numbers. Dense and banded matrices are handled, but not general sparse matrices. In all areas, similar functionality is provided for real and complex matrices, in both single and double precision. LAPACK in vecLib makes full use of the optimized BLAS and fully benefits from their performance. All the industry standard FORTRAN LAPACK entry points are exported from the vecLib framework. C programs may make calls to the FORTRAN entry points using the prototypes set out in "/System/Library/Frameworks/vecLib.framework/Headers/clapack.h". For more information refer to <http://www.netlib.org/lapack/ index.html>. BLAS and LAPACK follow fortran calling conventions (even from C). Users must be aware that: ALL arguments must be passed by reference. This includes all scalar arguments such as matrix dimension M and N, further note there is a difference in the memory arrangement of a two-dimensional array in Fortran and C. For more information refer to <http://www.netlib.org/clapack/readme>. -- To post to this group, send an email to sage-devel@googlegroups.com To unsubscribe from this group, send an email to sage-devel+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/sage-devel URL: http://www.sagemath.org
