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.
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Can I use MKL from Java, From C# or from Python or from ......? Many developers may ask the first question when learn Intel MKL. The answer isYES. Then a following question is how to?
Here is briefintrodution about how to use:
Intel MKL is composed of a set of libraries, which support C/C++ and Fortran language. When use MKL from other languages like Java, from C# or from Python, the common method is to build a custom dll based onthe set of mkl libraries. (A build tool is available in the tools/builder sub-directory of the Intel MKL package)
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:
- if I want all eigenvalues (-DSEGFAULT), I get a segfault inside the call to dstebz,
- 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.
I want to compute a 1d fft with dfti.
Here is my code
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?
Thanks in advanced,
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.
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
and the true covariance matrix is
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.
What are the chances of seeing scalapack in mkl for Mac OS X in near future?
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