Math Kernel Library

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  1. Intel® Math Kernel Library (Intel® MKL) accelerates math processing and neural network routines that increase application performance and reduce development time.[1]
  2. Intel MKL includes highly vectorized and threaded Linear Algebra, Fast Fourier Transforms (FFT), Neural Network, Vector Math and Statistics functions.[1]
  3. Using Intel MKL can save development, debug and maintenance time in the long run because today's code will run optimally on future generations of Intel processors with minimal effort.[1]
  4. The Intel Math Kernel Library (MKL) is a library of optimized, general-purpose math software.[2]
  5. the MKL module gives you access to many MKL examples.[2]
  6. This example shows how to use the Intel compiler ifort to compile a program with MKL dependencies.[2]
  7. The program in this example calls BLAS subroutine DGEMM, which is included in MKL.[2]
  8. Intel Math Kernel Library (Intel MKL) is a library of optimized math routines for science, engineering, and financial applications.[3]
  9. MKL is bundled with Intel Parallel Studio XE, Intel Cluster Studio XE, Intel C++, Fortran Studio XE products as well as canopy.[3]
  10. At least two routes for hooking the MKL's internal routines to remove the discrimination have been discovered.[3]
  11. Agner Fog discovered that MKL and ICC binaries also have a non-discriminating dispatcher.[3]
  12. MKL 9.0 release is included with the product ( <install_dir> /Documentation/ja-JP/mklman90.pdf).[4]
  13. Available only if the Intel® C++ Composer XE or Intel® Fortran Composer XE product that includes Intel MKL provides Japanese localization.[4]
  14. MKL includes a wealth of routines to accelerate technical application performance on modern multicore architectures.[5]
  15. If you are mixing an Anaconda environment with modules to build, always activate the conda environment before loading any library modules like MKL.[5]
  16. With the Intel toolchain, linking against MKL is as simple as adding -mkl to the link command.[5]
  17. This by default links in the threaded MKL routines.[5]
  18. Intel® Math Kernel Library (Intel® MKL) helps you achieve maximum performance with a math computing library of highly optimized, extensively threaded routines.[6]
  19. Select a function or routine from the Intel MKL library that is best suited for your problem.[6]
  20. The release notes contain information specific to the latest release of Intel MKL including new and changed features.[6]
  21. Providers become interesting when they can leverage a platform-native high performance library like Intel MKL instead of the default purely managed provider.[7]
  22. However, native binaries like our MKL provider are platform specific, so we need to load them with services of the platform instead of the .Net runtime.[7]
  23. This means that you can, for example, place the 32 bit MKL provider binaries into C:\MKL\x86 and the 64 bit ones into C:\MKL\x64 , and then set Control.[7]
  24. and /x64 folders in mathnet-numerics/out/MKL: you should now find the libiomp5.dylib and MathNet.Numerics.MKL.dll libaries.[7]
  25. ® Math Kernel Library (Intel® MKL) (shown in the last lines of code in the figure).[8]
  26. Replacing the Intel MKL routine with a simpler numerical integration routine allows us to solve both of these problems.[8]
  27. The DGEMM provided by Intel MKL is already cache-blocked, solving all of the issues experienced by our implementation.[8]
  28. For multi-process applications, we also support the ScaLAPACK, FFTW2, and FFTW3 MKL wrappers.[9]
  29. You can use module spider mkl to view available modules for a given machine.[9]
  30. To load the default MKL, run the following command: module load mkl .[9]
  31. To load a particular version, use module load mkl/version .[9]
  32. Load the appropriate mkl module, and then link your code using an appropriate link line.[10]
  33. Never load the MKL modules automatically in your shell startup files.[10]
  34. For older versions of MKL they have to be compiled.[10]
  35. The Intel Math Kernel Library (MKL) has been installed for use on Linux systems and can be loaded using the modules environment.[11]
  36. The MKL library is composed of highly optimized mathematical routines.[11]
  37. The link line for binding MKL to your application depends on the MKL functions used and if parallel or sequential use is required.[11]
  38. The Intel Math Kernel Library (MKL) is available, and we strongly recommend using it.[12]
  39. Several versions of MKL may exist, you can see which versions are available with the "module avail" command.[12]
  40. The MKL consists of two parts: a linear algebra package and processor specific kernels.[12]
  41. If you want to build an application using MKL with the Intel compilers at NSC, we recommend using the flag -Nmkl (to get your application correctly tagged) and the flag -mkl=MKLTYPE .[12]
  42. MKL's configuration settings for training and inference are influenced by these factors.[13]
  43. This is compared to the binary without MKL optimizations and measured in terms of samples/second.[13]
  44. In rare cases Intel MKL can have adverse effects.[13]
  45. ® Math Kernel Library (Intel® MKL) optimizes code with minimal effort for future generations of Intel® processors.[14]
  46. Technical support For details about the compiler and linking options, threading, and memory management with Intel MKL , see Intel MKL User's Guide.[15]
  47. Math Kernel Library Help bookmark in the left-hand panel and then the Intel Math Kernel Library Reference Manual bookmark below it.[15]
  48. ® Math Kernel Library (Intel® MKL) includes a wealth of math processing routines to accelerate application performance and reduce development time.[16]
  49. Intel® MKL includes highly vectorized and threaded Linear Algebra, Fast Fourier Transforms (FFT), Vector Math and Statistics functions.[16]
  50. “I’m a C++ and Fortran developer and have high praise for the Intel® Math Kernel Library.[16]
  51. ® MKL includes highly vectorized and threaded Linear Algebra, Fast Fourier Transforms (FFT), Vector Math and Statistics functions.[16]
  52. Update build scripts so that they point to the desired version of Intel MKL if you choose to keep multiple versions installed on your computer.[17]
  53. Note that you can have several versions of Intel MKL installed on your computer, but you will be required to remove beta versions of this software.[17]
  54. If you want to further customize some Intel MKL features, you may use the configuration file mkl.cfg which contains several variables that can be changed.[17]
  55. Now we need to download the MKL package.[18]
  56. In the example, a matrix multiplication is performed using the optimized function cblas_dgemm included in MKL.[18]
  57. The Math Kernel Library (MKL) patch will fix the Math Kernel Library used by LabVIEW Analysis VIs.[19]
  58. The Intel Math Kernel Library (MKL) is composed of highly optimized mathematical functions for engineering and scientific applications requiring high performance on Intel platforms.[20]
  59. The sequential (non-threaded) mode does not require an OpenMP runtime library, and does not respond to the environment variable OMP_NUM_THREADS or its Intel MKL equivalents.[20]
  60. In this mode, Intel MKL runs unthreaded code.[20]
  61. You should use the library in the sequential mode only if you have a particular reason not to use Intel MKL threading.[20]
  62. The Intel Math Kernel Library (MKL) is a set of math libraries that contains optimized BLAS, LAPACK, FFTs, ScaLAPACK and other functions.[21]
  63. It is quite simple to compile and link a C, C++, or Fortran program with Intel MKL, especially when using the Intel compilers.[21]
  64. The Intel MKL comes bundled with Intel compilerand Intel MPI.[21]
  65. To link MKL with non-Intel compiler toolchain, additional environment variables and linking options are required.[21]
  66. MKL provides linear algebra routines, fast fourier transform, vector math library function, and random number generator function, for developers of engineering, science, and financial software.[22]
  67. When using MKL, you need to use the Intel compiler.[22]
  68. BLACS and SCALAPACK in MKL cannot be used since MKL doesn't support Cray MPI.[22]
  69. 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.[23]
  70. 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.[23]
  71. The desired compiler module (exception system GNU compiler) has to be loaded before using MKL.[23]
  72. To see a list of all MKL environments set by the 'module load'-command use 'env | grep MKL'.[23]
  73. Intel’s Math Kernel Library (MKL) provides highly optimized, threaded and vectorized functions to maximize performance on each processor family.[24]
  74. The MKL was installed along with the Intel compilers as part of Intel Parallel Studio.[24]
  75. The purpose of this set of wrappers is to enable developers whose programs currently use FFTW to gain performance with the Intel MKL Fourier transforms without changing the program source code.[25]
  76. However, the wrappers to these functions and the fftw_cleanup_threads wrapper are empty and do nothing, as the Intel MKL DFTI implements a different mechanism of parallelization.[25]
  77. Then the FFTW library can be substituted by the wrapper and Intel MKL libraries.[25]
  78. The file fftw3_f77_mkl.h in the \interfaces\fftw3xf\wrappers subdirectory in the Intel MKL directory defines function names according to names in the Fortran module.[25]

소스

  1. ↑ 1.0 1.1 1.2 Download Intel's Math Kernel Library
  2. ↑ 2.0 2.1 2.2 2.3 Math Kernel Library (MKL)
  3. ↑ 3.0 3.1 3.2 3.3 Math Kernel Library
  4. ↑ 4.0 4.1 Intel® Math Kernel Library Documentation
  5. ↑ 5.0 5.1 5.2 5.3 Using the Intel Math Kernel Library on Eagle
  6. ↑ 6.0 6.1 6.2 Get Started with Intel® Math Kernel Library 2020 for Linux*
  7. ↑ 7.0 7.1 7.2 7.3 Intel Math Kernel Library (MKL)
  8. ↑ 8.0 8.1 8.2 Intel Math Kernel Library - an overview
  9. ↑ 9.0 9.1 9.2 9.3 MKL - Intel Math Kernel Library
  10. ↑ 10.0 10.1 10.2 Intel Math Kernel Library
  11. ↑ 11.0 11.1 11.2 Intel Math Kernel Library — Max Planck Computing & Data Facility
  12. ↑ 12.0 12.1 12.2 12.3 Math libraries
  13. ↑ 13.0 13.1 13.2 AWS Deep Learning Containers Intel Math Kernel Library (MKL) Recommendations
  14. ↑ Intel® Math Kernel Library (MKL) – Polyhedron Software & Services Ltd. Website
  15. ↑ 15.0 15.1 Intel® Math Kernel Library 9.1 for Linux*
  16. ↑ 16.0 16.1 16.2 16.3 Intel Math Kernel Library
  17. ↑ 17.0 17.1 17.2 Getting Started with the Intel(R) Math Kernel Library 8.1 for Linux*
  18. ↑ 18.0 18.1 Intel Math Kernel Library on Arduino
  19. ↑ Archived: Math Kernel Library (MKL) Patch Details
  20. ↑ 20.0 20.1 20.2 20.3 Intel Math Kernel Library (MKL)
  21. ↑ 21.0 21.1 21.2 21.3 Intel Math Kernel Library(MKL)
  22. ↑ 22.0 22.1 22.2 Intel Math Kernel Library
  23. ↑ 23.0 23.1 23.2 23.3 Math Kernel Library (MKL)
  24. ↑ 24.0 24.1 Intel Math Kernel Library — Sheffield HPC Documentation
  25. ↑ 25.0 25.1 25.2 25.3 FFTW3.x to Intel(R) Math Kernel Library Wrappers

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Spacy 패턴 목록

  • [{'LOWER': 'math'}, {'LOWER': 'kernel'}, {'LEMMA': 'Library'}]
  • [{'LEMMA': 'MKL'}]
  • [{'LOWER': 'intel'}, {'LOWER': 'math'}, {'LOWER': 'kernel'}, {'LEMMA': 'Library'}]
  • [{'LOWER': 'intel'}, {'LEMMA': 'MKL'}]
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