Merge pull request #46 from hifirworks/chiao/prepare-v0.2.0

Chiao/prepare v0.2.0

CHANGELOG.md

@@ -8,7 +8,7 @@ We follow the [Semantic Versioning](https://semver.org/) policy, which uses `MAJ
 - `MINOR` version when you add functionality in a backwards compatible manner, and
 - `PATCH` version when you make backwards compatible bug fixes.
 
-## v0.2.0 (TBD) ##
+## [v0.2.0](https://github.com/hifirworks/hifir/releases/tag/v0.2.0) (TBD) ##
 
 Changes from [v0.1.0](https://github.com/hifirworks/hifir/releases/tag/v0.1.0) to v0.2.0:
 
@@ -23,7 +23,7 @@ Changes from [v0.1.0](https://github.com/hifirworks/hifir/releases/tag/v0.1.0) t
 - Added MatrixMarket file readers for the C library.
 - Added example code for `libhifir`.
 
-[Full Changelog](https://github.com/hifirworks/hifir/compare/v0.1.0...HEAD)
+[Full Changelog](https://github.com/hifirworks/hifir/compare/v0.1.0...v0.2.0)
 
 ## [v0.1.0](https://github.com/hifirworks/hifir/releases/tag/v0.1.0) (2021-08-22) ##
 

README.md

@@ -43,6 +43,7 @@ Optionally, one can also use the C interface by building the runtime library `li
 ### Third-Party Dependency: LAPACK ###
 
 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
+
 ```console
 sudo apt install libopenblas-dev
 ```
@@ -53,9 +54,9 @@ and
 sudo yum install libopenblas-devel
 ```
 
-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.
+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.
 
-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.
+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.
 
 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.
 
@@ -88,7 +89,7 @@ If you plan to use HIFIR in solving singular and ill-conditioned systems, please
 ```bibtex
 @Article{jiao2022approximate,
   author  = {Xiangmin Jiao and Qiao Chen},
-  journal = {SIAM J. Matrix Anal. Appl},
+  journal = {SIAM J. Matrix Anal. Appl.},
   title   = {Approximate generalized inverses with iterative refinement for
              $\epsilon$-accurate preconditioning of singular systems},
   year    = {2022},
@@ -100,13 +101,13 @@ If you plan to use HIFIR in solving singular and ill-conditioned systems, please
 ```
 
 ```bibtex
-@Article{chen2021hifir,
+@Article{chen2022hifir,
   author  = {Chen, Qiao and Jiao, Xiangmin},
   title   = {{HIFIR}: Hybrid incomplete factorization with iterative refinement
              for preconditioning ill-conditioned and singular systems},
-  journal = {arXiv},
-  year    = {2021},
-  note    = {arXiv:2106.09877}
+  journal = {ACM Trans. Math. Softw.},
+  year    = {2022},
+  doi     = {10.1145/3536165}
 }
 ```
 

docs/doxygen/contents/main.doc

@@ -55,7 +55,7 @@ please cite the following papers.
 \verbatim
 @Article{jiao2022approximate,
   author  = {Xiangmin Jiao and Qiao Chen},
-  journal = {SIAM J. Matrix Anal. Appl},
+  journal = {SIAM J. Matrix Anal. Appl.},
   title   = {Approximate generalized inverses with iterative refinement for
              $\epsilon$-accurate preconditioning of singular systems},
   year    = {2022},
@@ -67,13 +67,13 @@ please cite the following papers.
 \endverbatim
 
 \verbatim
-@Article{chen2021hifir,
+@Article{chen2022hifir,
   author  = {Chen, Qiao and Jiao, Xiangmin},
   title   = {{HIFIR}: Hybrid incomplete factorization with iterative refinement
              for preconditioning ill-conditioned and singular systems},
-  journal = {arXiv},
-  year    = {2021},
-  note    = {arXiv:2106.09877}
+  journal = {ACM Trans. Math. Softw.},
+  year    = {2022},
+  doi     = {10.1145/3536165}
 }
 \endverbatim