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.
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?
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?
I'm trying to find the fastest way to do a multithreaded sparse matrix-vector multiply. I've written some benchmarking code to form a large random sparse matrix in CSR format, and then time 3 different implementations to compute y = y + A*x. I have a serial implementation, an openMP implementation, and mkl_dcsrmv. I'm computing the average and minimum time over a number of runs, say, 10.
at the moment I use dsyevd to compute the eigenvalues and eigenvectors of a large matrix A (n = 22000). This takes about half an hour. I know that they are a lot of zeros in matrix A (90% are zeros). Matrix A is stored as CSR sparse matrix.
- Is there a function to compute the eigenvalues and eigenvectors of a CSR sparse matrix?
- Is there a function to convert a CSR sparse matrix to a band matrix? Then I could use dsbevd.
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