intel-mkl

问题 I have installed intel mkl library. contents have path /home/user/intel/..... . I have to run a C++ code using make file on which it is mentioned. CC = /home/user/intel/bin/icpc -g INCLUDE = -I/home/user/intel/mkl/include LIB = -L/home/user/intel/mkl/lib/intel64 -lmkl_core -lmkl_intel_lp64 -lmkl_intel_thread -liomp5 -lpthread -std=c++11 I have successfully installed parallel_studio_xe_2019_update5_cluster_edition . but still I'm getting an error message that ./main :error while loading shared

问题 I want to use intel mkl in some optimazation problems, so I use intel example to test it. test.cpp: #include <mkl.h> #include <stdio.h> typedef struct { double re; double im; } complex16; extern "C" void cblas_zdotc_sub(int, const void*, int, const void*, int, void*); #define N 5 int main() { int n, inca = 1, incb = 1, i; complex16 a[N], b[N], c; n = N; for(i = 0; i < n; i++) { a[i].re = (double)i; a[i].im = (double)i * 2.0; b[i].re = (double)(n - i); b[i].im = (double)i * 2.0; } cblas_zdotc

问题 I have a code with following structure #pragma omp parallel { #omp for nowait { // first for loop } #omp for nowait { // first for loop } #pragma barrier <-- #pragma omp single/critical/atomic --> not sure dgemm_(....) #pragma omp for { // yet another for loop } } For dgemm_, I link with multithreaded mkl. I want mkl to use all available 8 threads. What is the best way to do so? 回答1: This is a case of nested parallelism. It is supported by MKL, but it only works if your executable is built

问题 I love being able to use Christoph Gohlke's numpy-MKL version of NumPy linked to Intel's Math Kernel Library on Windows. However, I have been unable to find a similar version for OS X, preferably NumPy 1.7 linked for Python 3.3 on Mountain Lion. Does anyone know where this might be obtained? EDIT: So after a bit of hunting I found this link to evaluate Intel's Composer XE2013 studios for C++ and Fortran (both of which contain the MKL), as well as a tutorial on building NumPy and SciPy with it

问题 I love being able to use Christoph Gohlke's numpy-MKL version of NumPy linked to Intel's Math Kernel Library on Windows. However, I have been unable to find a similar version for OS X, preferably NumPy 1.7 linked for Python 3.3 on Mountain Lion. Does anyone know where this might be obtained? EDIT: So after a bit of hunting I found this link to evaluate Intel's Composer XE2013 studios for C++ and Fortran (both of which contain the MKL), as well as a tutorial on building NumPy and SciPy with it

问题 I am inverting a matrix via a Cholesky factorization, in a distributed environment, as it was discussed here. My code works fine, but in order to test that my distributed project produces correct results, I had to compare it with the serial version. The results are not exactly the same! For example, the last five cells of the result matrix are: serial gives: -250207683.634793 -1353198687.861288 2816966067.598196 -144344843844.616425 323890119928.788757 distributed gives: -250207683.634692

问题 I use Eigen 3.3 and Intel MKL 2017, and write and run program in Visual Studio 2012 with Win-7 64-bit system and Intel Xeon(R) CPU E5-1620 v2@3.70GHZ CPU. I belive that my configuration for MKL is correct, because I can succesfully run MKL examlpe codes. The configuraton for using Intel MKL from Eigen follows from https://eigen.tuxfamily.org/dox/TopicUsingIntelMKL.html. For Visiual Studio 2012, I complie codes via Intel C++ Complier in Release x64 model. However, the following code always

问题 According to the Enthought website, the EPD Python distribution uses MKL for numpy and scipy. Does EPD Free also use MKL? If not does it use another library for BLAS/LAPACK? I am using EPD Free 7.3-2 Also, what library does the windows binary installer for numpy that can be found on scipy.org use? 回答1: The EPD Free 7.3 installers do not include MKL. The BLAS/LAPACK libraries which they use are ATLAS on Linux & Windows and Accelerate on OSX. 回答2: According to this table, EPD Free 7.3 does not

问题 I've a following up question to What is the stack size of a BackgroundWorker DoWork Thread? Is there way to change it? Should I increase the stack size of my main program using the following post build event: "$(DevEnvDir)..\..\VC\bin\editbin.exe" /STACK:8388608 "$(TargetPath)" or should I capsule my recursive code block inside a new thread with a larger stack size? Thread thread = new Thread(delegate() { // do work with larger stack size }, 8192 * 1024); thread.Start(); thread.Join(); The

问题 Before I start, let me put alternative titles for this post: How to compile CVXOPT with Intel MKL ? How to change __init__.py in CVXOPT to compile with Intel MKL ? Let me explain the issue. I am trying to install pystruct with Enthought python because Enthought python provides significant speed up in comparison to python in the Ubuntu package manager. The speed-up are mostly due to compiling back-end linear algebra libraries with Intel MKL libraries. I have to say that CVXOPT and pystruc