lapack

I have a working LAPACK implementation and that, as far as I read, contains BLAS. I want to use SPARSE BLAS and as far as I understand this website , SPARSE BLAS is part of BLAS. But when I tried to run the code below from the sparse blas manual using g++ -o sparse.x sparse_blas_example.c -L/usr/local/lib -lblas && ./sparse_ex.x the compiler (or linker?) asked for blas_sparse.h. When I put that file in the working directory I got: ludi@ludi-M17xR4:~/Desktop/tests$ g++ -o sparse.x sparse_blas_example.c -L/usr/local/lib -lblas && ./sparse_ex.x In file included from sparse_blas_example.c:3:0:

When I try to import numpy, I get the following error: /usr/local/lib/python2.7/dist-packages/numpy/linalg/__init__.py in <module>() 49 from .info import __doc__ 50 ---> 51 from .linalg import * 52 53 from numpy.testing import Tester /usr/local/lib/python2.7/dist-packages/numpy/linalg/linalg.py in <module>() 27 ) 28 from numpy.lib import triu, asfarray ---> 29 from numpy.linalg import lapack_lite, _umath_linalg 30 from numpy.matrixlib.defmatrix import matrix_power 31 from numpy.compat import asbytes ImportError: /usr/lib/liblapack.so.3: undefined symbol: gotoblas I have already tried solutions

I want build levmar-2.5 math library on a mac using the included Makefile. It requires LAPACK, another math library which is included in the Accelerate Framework. I do not know how to modify the Makefile to indicate the location of the library so that it builds correctly. There is a libLAPACK.dylib in the framework. Ultimately, I will want to use this library to build another library. Also I am not sure if there will be a problem mixing .so and .dylib dynamic libraries. Thank you. The project is located at levmar . Here is the Makefile: # # Unix/Linux GCC Makefile for Levenberg - Marquardt

I have been exploring algorithms that require some work on matrices, and I have gotten some straightforward code working on my Linux machine. Here is an excerpt: extern "C" { // link w/ LAPACK extern void dpptrf_(const char *uplo, const int *n, double *ap, int *info); extern void dpptri_(const char *uplo, const int *n, double *ap, int *info); // BLAS todo: get sse2 up in here (ATLAS?) extern void dgemm_(const char *transa, const char *transb, const int *m, const int *n, const int *k, const double *alpha, const double *a, const int *lda, const double *b, const int *ldb, const double *beta,

I would like to use Visual Studio 2008 , programming in C++, but would also like to use LAPACK power, Is there any wrapper so I can use LAPACK in Visual Studio 2008 . Check out CLAPACK , lapack++ , or its supposed successor Template Numerical Toolkit . Armadillo works great for me. Good API, excellent performance. I use this: https://svn.boost.org/svn/boost/sandbox/numeric_bindings/ careful not to use the old v1: http://boost.2283326.n4.nabble.com/binding-v1-vs-sandbox-numeric-bindings-td3036149.html If you are willing to use a commercial product, then I can recommend Intel Math Kernel library

If I use scipy.linalg.solve (which I believe calls LAPACK's gesv function) on a ~12000 unknown problem (with a ~12000-square, dense, non-symmetrical matrix) on my workstation, I get a good answer in 10-15 minutes . Just to probe the limits of what's possible (note I don't say "useful"), I doubled the resolution of my underlying problem, which leads to needing to solve for ~50000 unknowns. While this would technically run on my workstation once I'd added some more 10s of GBytes of swap, it seemed more prudent to use some HW with adequate RAM, and so I kicked it off on an AWS EC2 High-Memory