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Package Request: python-numpy-mkl #718
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我估计不会有人打包。因为依赖 不过之前我倒是写过一篇帖子,可以把系统里的 lapack/blas/cblas/fftw 都换成 mkl 的,这样编译时依赖这堆计算库的程序(比如 octave/numpy/torch 等)默认都会使用 mkl。 http://bbs.archlinuxcn.org/viewtopic.php?id=4418 |
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哦,忘了,年代久远可能记错了吧…… |
这个numpy的并行能力与官方源的相比有肉眼可见的巨大提升,官方的基本是一核有难七核围观。。非常希望archlinuxcn能提供prebuilt版本,不过如果的确部署困难或者eula不允许mkl再分发或者其他原因导致不能收录,请关闭这个issue。 |
或者考慮讓 arch4edu 加?他們已經有打包 intel-parallel-studio-xe 了或許會容易點。 https://github.com/arch4edu/arch4edu |
arch4edu 倒是提供 icc 全家桶,不过好像没有 numpy-mkl。如果在源里有人收养 icc 全家桶和 numpy-mkl 前你要用到的话,可以先暂时用下那边的 mkl。XD |
@farseerfc 前辈抢我台词…… |
问题类型 / Type of issues
NumPy automatically maps operations on vectors and matrices to the BLAS and LAPACK functions wherever possible. Since Intel® MKL supports these de-facto interfaces, NumPy can benefit from Intel MKL optimizations through simple modifications to the NumPy scripts.
https://aur.archlinux.org/packages/python-numpy-mkl/
http://www.numpy.org/
https://software.intel.com/en-us/articles/numpyscipy-with-intel-mkl
NumPy is widely used in many computer science areas, especially machine learning. As seen in Intel's document, it runs much faster on Intel processors when built with Intel® Math Kernel Library. However, the toolchain is large and not frequently used. A prebuilt version can help a lot.
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