Intel® Math Kernel Library

MKL reproductibility

Is there any way to get deterministic results from MKL sgemm/dgemm (even if that is much slower)?

What I mean is the following: When I do dgemm or sgemm (a lot of them) using the same input data I tend to see minor numerical differences. While not being large they can become quite significant when back-propagating though a very deep neural network (>20 layers). And they are significantly higher than with competing linear algebra packages.

Nonlinear optimization with a matrix form of constraints

I'm trying to solve a nonlinear optimization problem with a matrix for linear constratins using MKL (Intel C++ 16.0).

Although aware that some bounds can be set for each variable x_i, e.g., LB_i <= x_i <= UB_i (like the usage example),

not quite sure how to impose additional constratins in matrix forms such that: Ax = b where A is m-by-n matrix; i.e. there are m constraints for variables x.

Intel MKL FATAL ERROR: Error on loading function mkl_blas_avx_xdcopy


Hi experts

I am trying compile Bonmin (An mathematical programming software) using icc, icpc and  mkl from Intel System Studio 2016 (on Opensuse Linux 13.1). Bonmin requires lapack and blas functions. So, I am compiling Bonmin using:

-L/opt/intel/lib/intel64/ -L/opt/intel/compilers_and_libraries/linux/mkl/lib/intel64/  -lmkl_intel_lp64  -lmkl_sequential   -lmkl_core  -liomp5  -lpthread -lm

The compilation seems work fine. I got an executable called Bonmin. However, when I try run Bonmin, I get the following error message:

MKL inspector-executor mkl_sparse_optimize returns SPARSE_STATUS_NOT_SUPPORTED

I'm trying to get a test program working with the MKL inspector-executor framework, but I'm getting the rather opaque error code SPARSE_STATUS_NOT_SUPPORTED from mkl_sparse_optimize and it isn't clear what I'm doing wrong. I was hoping I could get some help. Below is a snippet of my code:

MKL_pardiso weird behaviour with large matrices

Hello, everybody.

Still trying to solve very large systems of sparse equations with `mkl pardiso`, single node, multiple thread version. The solver is behaving really well for small systems, but not so much for larger equations. In our case, scalability is essential.

With a large enough system of linear equations (79999 x 79999, 100528321 non-zeros), the sovler returns a vectors of `-nan`s, without reporting any errors. The expected result is provided (`expected-result.txt`).

Can't get pardiso to multithread (MKL linking issue?)

Hello, I'm currently trying to get pardiso to work with multi threading and I'm wondering if it is a linking issue or something else. I have tried some "easy" fixes that didn't work, then I tried the link advisor and get an error when linking.

Question: How do I get pardiso to work with multiple cores?


When calling pardiso I use the following iparm

Cluster Sparse Solver(cpardiso) reordering problem


I tried to solve a large linear equation (1,000,000 x 1,000,000 / bandwidth = 100 or 1000) with cpardiso.

( the matrix type is real and symmetric indefinite. )

I have some problems about reordering time and memory.

CPARDISO's reordering phase is compare to slower than the other phase. So I checked event time using Traceanalyzer.

CPARDISO used only one process(rank 0) for reordering and Rank 0 collected information on the divided A matrix on each process.

mkl_lapack_ao_zgeqrf not located

I am running the Intel Compiler 16.0 in Visual Studio Professional 2013. I have a project that I wish to make as an x64 executable. I am able to compile and run the Win32 version, and I can compile and link the x64 version, but when I try to run it I get the message:

The procedure entry point mkl_lapack_ao_zgeqrf could not be located in the dynamic link library G:\Program Files(x86)\VNI\imsl\fnl701\Intel64\lib\imslmkl_dll.dll.

WordSize of SFMT19937

While generating integer sequences of n elements using the the SFMT19937 BRNG, I noticed that the output consisted of exactly n elements, while I should have received 4n elements, according to the Intel VSL Notes documentation.

I also found that the SFMT19937 WordSize obtained from the VSLBrngProperties struct returns 4, when I expected this to be 16.

Is this the correct behavior for the SFMT19937 BRNG?  If so, how would I go about obtaining all 128 bits of output?




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