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@@ -43,6 +43,7 @@ Optionally, one can also use the C interface by building the runtime library `li
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### Third-Party Dependency: LAPACK ###
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The only third-party dependency of HIFIR is LAPACK, which HIFIR uses for its dense-level factorization and solve. We recommend using [OpenBLAS](https://www.openblas.net/), [ATLAS](http://math-atlas.sourceforge.net/), or [Intel oneAPI Math Kernel Library](https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/onemkl.html) (formerly Intel MKL). Assuming you have system-administrator permussions, you can install OpenBLAS using the `apt` and `yum` command on Debian and RedHat-based Linux systems, such as
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```console
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sudo apt install libopenblas-dev
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```
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sudo yum install libopenblas-devel
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```
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If you prefer to use ATLAS, the corresponding libraries are `libatlas-dev` and `libatlas-devel` on Debian and RedHat-based systems, respectively. Note that if you have multiple versions of BLAS and LAPACK installed, you may need to use the `update-alternatives --config` or `alternatives --config` command to config your system for the proper versions of BLAS and LAPACK; see https://wiki.debian.org/DebianScience/LinearAlgebraLibraries and https://www.redhat.com/sysadmin/alternatives-command for more detail.
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If you prefer to use ATLAS, the corresponding libraries are `libatlas-dev` and `libatlas-devel` on Debian and RedHat-based systems, respectively. Note that if you have multiple versions of BLAS and LAPACK installed, you may need to use the `update-alternatives --config` or `alternatives --config` command to config your system for the proper versions of BLAS and LAPACK; see <https://wiki.debian.org/DebianScience/LinearAlgebraLibraries> and <https://www.redhat.com/sysadmin/alternatives-command> for more detail.
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For Intel MKL, please refer to https://software.intel.com/content/www/us/en/develop/articles/installing-intel-free-libs-and-python-apt-repo.html and https://software.intel.com/content/www/us/en/develop/articles/installing-intel-free-libs-and-python-yum-repo.html for installation on Debian and RedHat-based systems, respectively.
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For Intel MKL, please refer to <https://software.intel.com/content/www/us/en/develop/articles/installing-intel-free-libs-and-python-apt-repo.html> and <https://software.intel.com/content/www/us/en/develop/articles/installing-intel-free-libs-and-python-yum-repo.html> for installation on Debian and RedHat-based systems, respectively.
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For other platforms, please refer to the official documentation of [OpenBLAS](https://www.openblas.net), [ATLAS](http://math-atlas.sourceforge.net/faq.html#doc), [Intel MKL](https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/onemkl.html), or the vendor-provided LAPACK for your platform, respectively.
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```bibtex
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@Article{jiao2022approximate,
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author = {Xiangmin Jiao and Qiao Chen},
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journal = {SIAM J. Matrix Anal. Appl},
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journal = {SIAM J. Matrix Anal. Appl.},
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title = {Approximate generalized inverses with iterative refinement for
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$\epsilon$-accurate preconditioning of singular systems},
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year = {2022},
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```
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```bibtex
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@Article{chen2021hifir,
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@Article{chen2022hifir,
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author = {Chen, Qiao and Jiao, Xiangmin},
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title = {{HIFIR}: Hybrid incomplete factorization with iterative refinement
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for preconditioning ill-conditioned and singular systems},
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