Intel® Math Kernel Library

A bug in zgelsd in MKL 15.0

Hi there, 

Thank you for reading this post. 

I got these error messages when calling zgelsd  in MKL 15.0 to solve  a fairly large matrix,

Intel MKL INTERNAL ERROR: Condition 1 detected in function DLASD4.

Intel MKL INTERNAL ERROR: Condition 1 detected in function DLASD8.

I googled online and found the exact issue here, where it said the bug had been fixed in MKL 11 update 5.

multi-threaded matrix multiplication

Dear Intel MKL developers,

I am integrating the MKL subroutine mkl_zcsrmultcsr in my MPI code. I tested a case with 16 processors, and mkl_zcrsmultcsr is called in every processor in parallel. Once it is called, multi-threaded computing is automatically activated.

The problem I encountered is that 12 processors among all processors work fine while the other 4 processors give memory corruption errors, moreover, these 4 processors can vary during each test. I am not sure what the problem would be. Your advise is well appreciated.








Just noticed that the latest version of MKL (11.2 Update 2) has these comments in the release notes:

"Added ability to free up memory used by the input matrix after the factorization step. This helps to reduce memory consumption when iterative refinement is not needed and disabled by the user."

I want to try this, How can I do it? What I need to set?

It also says that "iterative refinement should be disabled".  Is setting "iparam[8]=0" sufficient for this?

Equivalent function NCONF/NLQPL

hello folks!

I am looking for an equivalent function to NCONF/DNCONF which has been defined in the IMSL library. Here is the description of this function:

Solve a general nonlinear programming problem using the successive quadratic programming algorithm and a finite difference gradient.


In nutshell, I have to minimize a multi-variable function knowing that one (or more) condition have to be accomplished.

Thank you in advance.


sparse 3D convolution

Hi MKL developers,

I am trying to implement a sparse convolution function based on MKL convolution. According to the sparseness, I departed the big convolution to a serials of subconvolution tasks. But only the first subconvolution result is correct, it goes wrong when I step forward in the sparseness.

Intel - Distribution - Program Fails

I'm trying to distribute some mkl files around for client use. Here's a quick synopsis of the problem.

1 - I have a Intel License Server running on a remote machine.

2 - I have some math libraries which get picked up in a ribbon for use in Excel.

3 - When I distribute the mkl libraries around and a client tries to run function which calls MKL in Excel, it crashes. Using the event logger and other logging tools have proven fruitless.

Things I've tried to resolved the issue.

Data fit dfdInterpolateEx1D function warning code

Hello everybody, I am having some problems with the dfdInterpolateEx1D function of the MKL Data Fit module. I am calling the above function, togheter with all the relative initialization/setting/clean function, within a loop and the results are sometimes corrects and sometimes wrong. Particularly, the wrong results provided by the above function are always equal to 0 and in correspondence to these events the error/warning status is equal to 10.

getrf & getrs caused a 'corrupted double-linked list' error


     We are using MKL calls dgetrf & dgetrs from MKL 11.2 Update 2 to solve linear systems of small size (typically 4 X 4 or 9 X 9 or 16 X 16). Here is how the program works - we need to perform computations with systems of different sizes. We allocate memory, compute, free and repeat as required. Eventually, after several allocate-compute-free cycles, when we free the dynamically allocated array 'a' in the documentation at 

Ivy Bridge (E5-2660 v2) processor and mkl_avx.dll

Dear Forum,

I have an Windows 7 application that uses Intel MKL libraries. I run it on the following two systems:

1). Sandy Bridge (E5-2660 0), and 

2). Ivy Bridge (E5-2660 v2)

I noticed, using Process Explorer, that on Sandy Bridge, mkl_avx.dll is loaded, while on Ivy Bridge, mkl_mc3.dll is loaded. Moreover, the performance on Ivy Bridge (w/ mkl_mc3.dll) is 15-30% worse than that on Sandy Bridge (w/ mkl_avx.dll).

From the following two article, seems to me that both systems support AVX, and Ivy Bridge is the more advanced of these two.

Assine o Intel® Math Kernel Library