I go this ex1.c file from Intel 11. However, when I execute it, it fails: [email protected]:~/konstantis$ ../mpich-install/bin/mpicc -o test ex1.c -I../intel/mkl/include ../intel/mkl/lib/intel64/libmkl_scalapack_ilp64.a -Wl,--start-group ../intel/mkl/lib/intel64/libmkl_intel_ilp64.a ../intel/mkl/lib/intel64/libmkl_core.a ../intel/mkl/lib/intel64/libmkl_sequential.a -Wl,--end-group ../intel/mkl/lib/intel64/libmkl_blacs_intelmpi_ilp64.a -lpthread -lm -ldl [email protected]:~/konstantis$ mpiexec -n 4 ./test { 0, 0}: On entry to DESCI{...

I am trying to learn how a Makefile should look like, when it comes to the flags, especially the linking ones. Here is my Makefile: OBJS = n.o SOURCE = n.cpp # HEADER = there are no header files, so I commented that OUT = test CXX = ../mpich-install/bin/mpic++ FLAGS...

I typically get the latest scientific Python packages from here. I noticed that there are two version of numpy made available - standard and MKL versions. My questions: How much of performance improvements do we actually get from switching to the MKL version? Does anyone have benchmarks after testing it...

I have a code with following structure : Eigen::MatrixXd function1(args) { #pragma omp parallel for for (args) //filling a matrix element-wise return matrix; } Eigen::MatrixXd function2(argument is function1 matrix) { #pragma omp parallel for for (args) //element-wise probabilities calculations on matrix from function1 return matrix; } Eigen::MatrixXd global_function(args) { Eigen::MatrixXd...

Currently I do not get any fundings for my PhD. As a consequence I can use the free MKL libraries. But that will change soon. I compiled IPOPT and other packages against the MKL libraries. What will haben if I do not have the licence anymore ? Are the packages...

Folks, I'm calling LAPACKE_dptsv If all arguments are 1d arrays, does it matter if I call the data LAPACK_ROW_MAJOR or LAPACK_COL_MAJOR ?...

Do anyone have any idea how can I rewrite eig(A,B) from Matlab used to calculate generalized eigenvector/eigenvalues? I've been struggling with this problem lately. So far: Matlab definition of eig function I need: [V,D] = eig(A,B) produces a diagonal matrix D of generalized eigenvalues and a full matrix V whose...

I have a question regarding cblas_dgemv. I am trying to understand how it works. And what I am possibly doing wrong. I have an array Matrix and then I try to read that matrix RowMajor and ColumnMajor. I am getting the expected result in the RowMajor Case; [6, 2, 4,...

I am trying to do a Column Vector multiplication with a Row Vector. Can I use dgemm? In other words D = A * B where D is a Matrix, A is a Column Vector and B is a Row Vector. I followed the documentation found here https://software.intel.com/en-us/node/520775. I cannot...

I'm trying to set the number of threads for numpy calculations with mkl_set_num_threads like this import numpy import ctypes mkl_rt = ctypes.CDLL('libmkl_rt.so') mkl_rt.mkl_set_num_threads(4) but I keep getting an segmentation fault: Program received signal SIGSEGV, Segmentation fault. 0x00002aaab34d7561 in mkl_set_num_threads__ () from /../libmkl_intel_lp64.so Getting the number of threads is no problem:...