Intel® Math Kernel Library

Visual Studio 2015 unresolved external symbol _snprintf

Hi,

My code compiles fine when using Visual Studio 2013, but when converting it to VS15, I get this error:

Error    LNK2001    unresolved external symbol _snprintf    FEBio2    C:\FEBio2_15\VS2013\mkl_core.lib(mkl_aa_fw_device_threading_params.obj)    1

Any suggestions?

Thanks,

Dave

Error MKLMPI_Get_wrappers, cluster MKL using gfortran, OpenMPI

I am trying to compile a program using the MKL (11.3, 2016.0.109) libraries with the gfortran (5.1.0) compiler and OpenMPI (1.8.5, compiled against gfortran 5.1.0).

I can successfully compile the program without any errors.

However, when executing my program I end up with this error:

Odd dgesv results

Hello,

I'm trying to refactor a piece of code that solves a simple Ax=b linear problem using MKL. From the manual, I saw that dgesv is the function I should call.

A is an n-by-n Jacobian matrix (with just 5 non-zero diagonals), while b and x are arrays of size n.

To solve the problem I use this snippet of code

MKL Library license requirement for R

Hi All

We need to use MKL with Open Source R. As I read over this site, that these libraries will be used during compilation stage of R. 

Could you confirm on the licensing requirement. Should we go for Single user named license or what? R will run on linux OS with Intel processors.

 

Thanks

Puneet

 

Using MPI parMETIS with cluster_sparse_solver

Hello.

I am optimizing the `cluster_sparse_solver` runtime. In my case, the majority of the runtime is taken by phase `11`, symbolic factorization, with METIS. Additionally, only a single node is used in an otherwise `MPI`-enabled application.

I was wondering if there is a way to use `parMETIS` for fill-reducing ordering, in order to benefit from the cluster environment. One thing that would help tremendously is the source code for `cluster_sparse_solver`.

The version of MKL in question is mkl 11.2u3, which was bundled with composer_xe 2015 3.187.

Thanks!

DftiCommitDescriptor hangs my application

Hi,

I've been struggling with this for a while, hope you can help.

I'm creating a shared library on Linux (Centos 6.7) using FFT's implemented with the MKL. My library works fine when used together with my own test program, but fails when used from a 3rd party application.

The problem has been pinned down to the FFT's. Print-output arrives on screen after calling DftiCreateDescriptor and DftiSetValue, and the status is 0. But when I subsequently call DftiCommitDescriptor the 3rd party application keeps running at 100% cpu and doesn't show any print-output anymore.

Performing DFTI along a single axis of 2D array

Hi there,

I have a 2D array where the axes are positions (x, y). I wish to perform a Fourier transform along the x axis alone resulting in an array (Kx, y), where Kx is momentum, the Fourier transform of x.

In python this is a simple command as you can pass which axis to perform the transform along as an argument to the FFT function.
Is there a way to do this with the MKL library?

Thanks very much,
Dylan

floating point exception solving a non-symmetric matrix

The floating point exception occurs when solving the attached non-symmetric matrix.

1 line: n

2nd line: index base (i.e. 0 based)

3rd line: nz

followed by all nonzeros in coordinate (i.e. triplet) format

Major version: 11
Minor version: 1
Update version: 1
Product status:  Product
Build: n20131010
Processor optimization: Intel(R) Advanced Vector Extensions (Intel(R) AVX) Enabled Processor

linux

Thanks,

Sam

Why no simple linear equation solver?

I looked in the INTEL MATH KERNEL library, and could not find a routine that just solves

A*X=B

where A is an N by N matrix, and X and B are vectors of length N.

They throw a lot of confusing **** at you, when you just want to solve a basic problem,

and dont have a system with special characteristics, like SPARSE, Band, Hermitian, etc.

 

So its impossible to just find a basic routine to give you a quick answer.

Or if its there, they sure don't bother to tell you where - - - -

 

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