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README.md

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@@ -75,11 +75,22 @@ The package also provides `mkl_fft.interfaces.numpy_fft` and `mkl_fft.interfaces
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To build `mkl_fft` from sources on Linux with Intel® OneMKL:
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- install a recent version of MKL, if necessary;
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- execute `source /path_to_oneapi/mkl/latest/env/vars.sh`;
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- execute `python -m pip install .`
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To build `mkl_fft` from sources on Linux with conda:
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- install `python` and `mkl-devel` in a conda environment;
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- execute `export MKLROOT=$CONDA_PREFIX`
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- execute `python -m pip install .`
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- create a virtual environemnt: `python3 -m venv fft_env`
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- activate the environment: `source fft_env/bin/activate`
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- install a recent version of OneMKL, if necessary
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- execute `source /path_to_oneapi/mkl/latest/env/vars.sh`
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- `git clone https://github.com/IntelPython/mkl_fft.git mkl_fft`
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- `cd mkl_fft`
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- `python -m pip install .`
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- `cd ..`
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- `python -c "import mkl_fft"`
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To build `mkl_fft` from sources on Linux with conda follow these steps:
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- `conda create -n fft_env python=3.12 mkl-devel`
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- `conda activate fft_env`
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- `export MKLROOT=$CONDA_PREFIX`
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- `git clone https://github.com/IntelPython/mkl_fft.git mkl_fft`
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- `cd mkl_fft`
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- `python -m pip install .`
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- `cd ..`
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- `python -c "import mkl_fft"`

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