Intel® Math Kernel Library

Rank updates to pardiso factorization

Hi,

Is it possible to do rank-1-updates of the factorization computed by pardiso? That is, given A = L D L^T, I need to be able to efficiently compute the decomposition of A + alpha w w^T (w is a vector)

I'm using this functionality in an interior-point algorithm for large-scale convex optimization.

Best,

Jens

Fortran FFT with MKL

I'm currently messing with some code that uses an old F77 looking FFT subroutine full of goto's and other nasty stuff. I have been looking around at using MKL's FFT routines, but I am having trouble finding some examples of how they are used. My current FFT routine uses only double precision data, so I don't need a FFT dealing with complex. Can anyone point me to any example code using a 2D MKL FFT routine? (possibly within /opt/intel/mkl/examples)

Thanks in advance!

(For any interested, here is the current FFT routine being used)

Cluster Pardiso error for iparm(24)=1

Hello all,

Last week I have been trying out Cluster Pardiso, testing various options and so on, and I found a problem. Cluster Pardiso fails with various error messages when I enable two-level factorization (that is iparm(24)=1).

The error can be easily reproduced in the following way:

1. Edit cl_solver_sym_sp_0_based_c.c example and add "iparm[23] = 0" at line 112 (or around there)

2. Recompile: mpiicc -mkl -mt_mpi cl_solver_sym_sp_0_based_c.c -o cl_solver_sym_sp_0_based_c

3. Run: export OMP_NUM_THREADS=2; mpirun -np 6 ./cl_solver_sym_sp_0_based_c

dcsrmm is throwing 'integer division by zero' after upgrading to 11.0 update 5

After updating the installed MKL version when attempting to avoid another bug we discovered, previously working code has started throwing division by zero errors after sparse matrices exceed a certain nonzero count. (Again using parallel 64bit MKL)

Unhandled exception at 0x000007FEDEC0DB3D (mkl_avx.dll) in TestSparseMultiply.exe: 0xC0000094: Integer division by zero.

Callstack:

     mkl_avx.dll!000007fedec0db3d()    Unknown
     mkl_intel_thread.dll!000007fee0549de3()    Unknown

performance of mkl in multithread application in numa memory architecture decreased

hi

i have a server with 80 logical core with NUMA memory architecture and windows server 2012. 

i want create one thread per each logical core and each thread execute fft, convolution,... Independently.

when i have less 5 thread, cpu usage of each involved core is 100 %

but when I create more than 5 thread in a one numa group, cpu usage start to decrease so that by adding each thread , cpu usage of total cores slightly reduced.

so that in the end , when i have 80 thread , cpu usage of all cores is between 30 to 40 percent.

Parameters for ?stemr

I have a problem where I need to calculate a number of eigenvectors and a different number of eigenvalues. Instead of calling dsyevr twice I plan on calling dsytrd -> dstemr * 2 -> dormtr. (Or alternatively stebz / stein)

However, I have noticed unexpected behavior regarding the eigenvector parameter (using 11.0 update 5, from C).

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