Development/MKL: Difference between revisions
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{{Softwarepage|numlib/mkl}} |
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! Navigation: [[BwHPC_Best_Practices_Repository|bwHPC BPR]] |
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! Description !! Content |
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| module load |
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| numlib/mkl |
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| License |
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| Commercial. See [https://software.intel.com/en-us/articles/end-user-license-agreement EULA]. |
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| Citing |
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| n/a |
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| Links |
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| [https://software.intel.com/en-us/intel-mkl Intel MKL Homepage] | [https://software.intel.com/en-us/articles/intel-math-kernel-library-documentation Online-Documentation] |
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| Graphical Interface |
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| No |
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= Description = |
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__FORCETOC__ |
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= Math Kernel Library (MKL) = |
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'''Intel MKL (Math Kernel Library)''' is a library of optimized math routines for numerical computations such as linear algebra (using BLAS, LAPACK, ScaLAPACK) and discrete Fourier Transformation. |
'''Intel MKL (Math Kernel Library)''' is a library of optimized math routines for numerical computations such as linear algebra (using BLAS, LAPACK, ScaLAPACK) and discrete Fourier Transformation. |
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With its standard interface in matrix computation and the interface of the popular fast Fourier transformation library fftw, MKL can be used to replace other libraries with minimal code changes. In fact a program which uses FFTW without MPI doesn't need to be changed at all. Just recompile it with the MKL linker flags. |
With its standard interface in matrix computation and the interface of the popular fast Fourier transformation library fftw, MKL can be used to replace other libraries with minimal code changes. In fact a program which uses FFTW without MPI doesn't need to be changed at all. Just recompile it with the MKL linker flags. |
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<br> |
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* [http://software.intel.com/en-us/articles/intel-math-kernel-library-documentation Online-Documentation] |
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= Compiling and linking = |
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'''Online documentation:''' http://software.intel.com/en-us/articles/intel-math-kernel-library-documentation |
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'''Local documentation:''' |
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There is some information in the module help file accessible via |
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<pre>$ module help numlib/mkl</pre> |
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and after loading the module, the environment variable $MKL_DOC_DIR points to the local documentation folder. Various examples can be found in $MKLROOT/examples. |
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'''Compiling and linking:''' |
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Compilation is possible with both GCC and Intel compilers but it is easier for Intel compilers, so this case is explained here. |
Compilation is possible with both GCC and Intel compilers but it is easier for Intel compilers, so this case is explained here. |
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After loading the compiler and the library module with |
After loading the compiler and the library module with |
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When linking the program you have to tell the compiler to link against the mkl library: |
When linking the program you have to tell the compiler to link against the mkl library: |
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<pre>$ icpc example_mkl.o -mkl</pre> |
<pre>$ icpc example_mkl.o -mkl</pre> |
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With the -mkl switch the intel compiler automatically sets the correct linker flags but you can specify them explicitly for example to enable static linking or when non-intel compilers are used. Information about the different options can be found at |
With the -mkl switch the intel compiler automatically sets the correct linker flags but you can specify them explicitly for example to enable static linking or when non-intel compilers are used. Information about the different options can be found at https://software.intel.com/en-us/node/438568 and especially helpful is the MKL link line advisor at https://software.intel.com/en-us/articles/intel-mkl-link-line-advisor. |
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By default $MKL_NUM_THREADS is set to 1 and so only one thread will be created, but if you feel the need to run the computation on more cores (after benchmarking) you can set $MKL_NUM_THREADS to a higher number. |
By default $MKL_NUM_THREADS is set to 1 and so only one thread will be created, but if you feel the need to run the computation on more cores (after benchmarking) you can set $MKL_NUM_THREADS to a higher number. |
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<br> |
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<br> |
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== FFTW Interface to Intel Math Kernel Library (MKL) == |
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Sometimes, [[FFTW|FFTW]] is not available on your cluster. You can use the MKL library |
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instead and include the FFTW functions, too. |
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Intel Math Kernel Library (MKL) offers FFTW2 and FFTW3 interfaces to Intel MKL Fast Fourier Transform and Trigonometric Transform functionality. The purpose of these interfaces is to enable applications using FFTW to gain performance with Intel MKL without changing the program source code. |
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'''Examples:''' |
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To include the proper header files use the compiler option |
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To help getting started we provide two C++ examples. The first one computes the square of a 2x2 matrix: |
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-I${MKL_INC_DIR}/fftw |
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<source lang="cpp"> |
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#include <iostream> |
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#include <mkl.h> |
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using namespace std; |
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If you want to link dynamically against the fftw functions you can just use the flag |
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int main() |
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-mkl |
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{ |
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double m[2][2] = {{2,1}, {0,2}}; |
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double c[2][2]; |
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but when using static linking you have to link against the correct library in the directory |
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for(int i = 0; i < 2; ++i) |
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${MKL_HOME}/interfaces/ |
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{ |
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for(int j = 0; j < 2; ++j) |
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cout << m[i][j] << " "; |
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cout << endl; |
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} |
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cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans, 2, 2, 2, 1.0, &m[0][0], 2, &m[0][0], 2, 0.0, &c[0][0], 2); |
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cout << endl; |
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for(int i = 0; i < 2; ++i) |
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{ |
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for(int j = 0; j < 2; ++j) |
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cout << c[i][j] << " "; |
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cout << endl; |
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} |
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return 0; |
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} |
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</source> |
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|} |
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And the second one does a fast Fourier transformation using the Intel MKL interface (DFTI): |
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<source lang="cpp"> |
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#include <iostream> |
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#include <complex> |
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#include <cmath> |
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#include <mkl.h> |
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using namespace std; |
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int main() |
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{ |
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const int N = 3; |
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complex<double> x[N] = {2, -1, 0.5}; |
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cout << "Input: " << endl; |
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for(int i = 0; i < N; i++) |
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cout << x[i] << endl; |
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DFTI_DESCRIPTOR_HANDLE desc; |
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DftiCreateDescriptor(&desc, DFTI_DOUBLE, DFTI_COMPLEX, 1, N); |
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DftiCommitDescriptor(desc); |
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DftiComputeForward(desc, x); |
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DftiFreeDescriptor(&desc); |
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cout << "\nOutput: " << endl; |
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for(int i = 0; i < N; i++) |
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cout << x[i] << endl; |
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cout << "\nTest the interpolation function f:" << endl; |
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for(int i = 0; i < N; i++) |
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{ |
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double t = i/(double)N; |
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complex<double> u(0, 2*M_PI*t); |
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complex<double> z = exp(u); |
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complex<double> w = 1.0/N * (x[0] + x[1]*z + x[2]*z*z); |
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cout << "f(" << t << ") = " << w << endl; |
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} |
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return 0; |
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} |
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</source> |
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|} |
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See the corresponding webpages: |
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[[Category:Numerical_libraries]] |
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* [https://software.intel.com/en-us/node/471410 FFTW Interface to Intel Math Kernel Library] |
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* [https://software.intel.com/de-de/node/471414 FFTW2 Interface to Intel Math Kernel Library] |
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* [https://software.intel.com/en-us/node/471456 FFTW3 Interface to Intel Math Kernel Library] |
Latest revision as of 00:08, 15 March 2023
The main documentation is available via |
Description | Content |
---|---|
module load | numlib/mkl |
License | Commercial. See EULA. |
Citing | n/a |
Links | Intel MKL Homepage | Online-Documentation |
Graphical Interface | No |
Description
Intel MKL (Math Kernel Library) is a library of optimized math routines for numerical computations such as linear algebra (using BLAS, LAPACK, ScaLAPACK) and discrete Fourier Transformation.
With its standard interface in matrix computation and the interface of the popular fast Fourier transformation library fftw, MKL can be used to replace other libraries with minimal code changes. In fact a program which uses FFTW without MPI doesn't need to be changed at all. Just recompile it with the MKL linker flags.
Compiling and linking
Compilation is possible with both GCC and Intel compilers but it is easier for Intel compilers, so this case is explained here. After loading the compiler and the library module with
$ module load compiler/intel $ module load numlib/mkl
you can include the MKL header file in your program:
#include <mkl.h>
Compilation is simple:
$ icpc -c example_mkl.c
When linking the program you have to tell the compiler to link against the mkl library:
$ icpc example_mkl.o -mkl
With the -mkl switch the intel compiler automatically sets the correct linker flags but you can specify them explicitly for example to enable static linking or when non-intel compilers are used. Information about the different options can be found at https://software.intel.com/en-us/node/438568 and especially helpful is the MKL link line advisor at https://software.intel.com/en-us/articles/intel-mkl-link-line-advisor.
By default $MKL_NUM_THREADS is set to 1 and so only one thread will be created, but if you feel the need to run the computation on more cores (after benchmarking) you can set $MKL_NUM_THREADS to a higher number.
FFTW Interface to Intel Math Kernel Library (MKL)
Sometimes, FFTW is not available on your cluster. You can use the MKL library instead and include the FFTW functions, too.
Intel Math Kernel Library (MKL) offers FFTW2 and FFTW3 interfaces to Intel MKL Fast Fourier Transform and Trigonometric Transform functionality. The purpose of these interfaces is to enable applications using FFTW to gain performance with Intel MKL without changing the program source code. To include the proper header files use the compiler option
-I${MKL_INC_DIR}/fftw
If you want to link dynamically against the fftw functions you can just use the flag
-mkl
but when using static linking you have to link against the correct library in the directory
${MKL_HOME}/interfaces/
See the corresponding webpages: