# Intel® Math Kernel Library 11.1 Update 2 is now available

Intel® Math Kernel Library (Intel® MKL) is a highly optimized, extensively threaded, and thread-safe library of mathematical functions for engineering, scientific, and financial applications that require maximum performance. The Intel MKL 11.1 Update 2 packages are now ready for download.

# Intel® MKL with Numpy, Scipy, Matlab, C#, Python, NAG and more

The following article explains on using Intel® MKL with Numpy/SciPy, Matlab, C#, Java, Python, NAG, Gromacs, Gnu Octave, PETSc, HPL, HPCC, IMSL etc.
• Apple OS X*
• Linux*
• Microsoft Windows* (XP, Vista, 7)
• .NET*
• C#
• C/C++
• Fortran
• Java*
• Python*
• Beginner
• Intermediate
• Intel® Math Kernel Library
• scipy
• numpy
• matlab mkl
• python mkl
• C# mkl
• java mkl
• hpl mkl
• nag mkl
• hpcc mkl
• imsl mkl
• gromacs mkl
• wrf mkl
• Development Tools
• Open Source
• Optimization
• # Problem with dstebz and dormtr (dense eigenvalue solver)

Hello,

I'm trying to solve a symmetric generalized eigenvalue problem with the BLAS Fortran bindings inside C and I'm facing two problem with the following piece of code:

1. if I want all eigenvalues (-DSEGFAULT), I get a segfault inside the call to dstebz,
2. I am not sure on how to call dormtr to get the correct eigenvectors of my original system.

This is a simple Neumann problem, so the first eigenvalue is 0, but the associated eigenvector should be constant and this is clearly not the case.

# Problem computation of1D FFT

I want to compute a 1d fft with dfti.

Here is my code

# vsrnguniform

Dear all,

Can vsrnguniform generate random multidimensional arrays or it just works for 1D arrays? I guess that one solution could be to generate a 1D array and after reshape it. However, I would like to know if this function can handle multidimensional arrays?

Crist.

# problem in computation of 2D FFT using two seperate real and imaginary arrays

Hi,

i want to compute FFT of a complex 2D array. So first i have tried it in 2 ways.

1) Directly using complex 2D array(real and imaginary interleaved) .

2) 2 seperate arrays(where real and imaginary are deinterleaved into 2 seperate arrays).

i found the output is different in both cases. can some one tell me if i do some thing wrong in the code.

# Problem with robust estimation of a covariance matrix.

Hi I have the matrix "x" and I want to compute the covariance matrix. The i column of the matrix stores the observations
of the i variable.

The matrix is
0.8147    0.9058
0.1270    0.9134
0.6324    0.0975
and the true covariance matrix is
0.1269   -0.0450
-0.0450    0.2198

I read the manual Summary Statistics Application Notes (page 32) that explains how to find  a Robust Estimation of a Variance- -
Covariance Matrix and I wrote the following code in C.

# Scalapack on Mac OS X

What are the chances of seeing scalapack in mkl for Mac OS X in near future?

# blacs for sgi mpt

I need to compile a software package which requires blacs, however since about composer_xe_2013.5.192 blacs seems to have disappeared from MKL (except blacs for intelmpi and MIC). Where do I get the libmkl_blacs_sgimpt_lp64.a for intel64 for the newest composer_xe?