| [LAPACK](http://www.netlib.org/lapack/) | LAPACK is written in Fortran90 and provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. |
| [LAPACK](http://www.netlib.org/lapack/) | LAPACK is written in Fortran90 and provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. |
| [LAPACKE](http://www.netlib.org/lapack/lapacke.html) | LAPACKE C Interface to LAPACK header files and library |
| [LAPACKE](http://www.netlib.org/lapack/lapacke.html) | LAPACKE C Interface to LAPACK header files and library |
| [LIBLINEAR](http://www.csie.ntu.edu.tw/~cjlin/liblinear/) | LIBLINEAR is a simple package for solving large-scale regularized linear classification and regression. It supports L2-regularized logistic regression, L2-loss support vector classification L1-loss support vector classification, L1-regularized L2-loss support vector classification, L1-regularized logistic regression L2-regularized L2-loss support vector regression, L1-loss support vector regression. |
| [LIBLINEAR](http://www.csie.ntu.edu.tw/~cjlin/liblinear/) | LIBLINEAR is a simple package for solving large-scale regularized linear classification and regression. It supports L2-regularized logistic regression, L2-loss support vector classification L1-loss support vector classification, L1-regularized L2-loss support vector classification, L1-regularized logistic regression L2-regularized L2-loss support vector regression, L1-loss support vector regression. |
| [mkl](http://software.intel.com/en-us/intel-mkl/) | Intel Math Kernel Library is a library of highly optimized, extensively threaded math routines for science, engineering, and financial applications that require maximum performance. Core math functions include BLAS, LAPACK, ScaLAPACK, Sparse Solvers, Fast Fourier Transforms, Vector Math, and more. |
| [MPI-LIBLINEAR](https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/distributed-liblinear/mpi/) | MPI LIBLINEAR is an extension of LIBLINEAR on distributed environments. The usage and the data format are the same as LIBLINEAR. It supports L2-regularized logistic regression, L2-regularized logistic regression, L2-regularized L2-loss linear SVM (primal trust-region Newton), L2-regularized L1-loss linear SVM (dual), L2-regularized logistic regression (primal limited common directions), L2-regularized L2-loss linear SVM (primal limited common directions). Module created by the PERMON Team (http://permon.it4i.cz). |
| [MPI-LIBLINEAR](https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/distributed-liblinear/mpi/) | MPI LIBLINEAR is an extension of LIBLINEAR on distributed environments. The usage and the data format are the same as LIBLINEAR. It supports L2-regularized logistic regression, L2-regularized logistic regression, L2-regularized L2-loss linear SVM (primal trust-region Newton), L2-regularized L1-loss linear SVM (dual), L2-regularized logistic regression (primal limited common directions), L2-regularized L2-loss linear SVM (primal limited common directions). Module created by the PERMON Team (http://permon.it4i.cz). |
| [NLopt](http://ab-initio.mit.edu/wiki/index.php/NLopt) | NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. |
| [NLopt](http://ab-initio.mit.edu/wiki/index.php/NLopt) | NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. |
| [OpenBLAS](http://xianyi.github.com/OpenBLAS/) | OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version. |
| [OpenBLAS](http://xianyi.github.com/OpenBLAS/) | OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version. |
