# Template:Installing BLAS and LAPACK

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The first thing you must have on your system is a BLAS implementation. "BLAS" stands for "Basic Linear Algebra Subroutines," and is a standard interface for operations like matrix multiplication. It is designed as a building-block for other linear-algebra applications, and is used both directly by our code and in LAPACK (see below). By using it, we can take advantage of many highly-optimized implementations of these operations that have been written to the BLAS interface. (Note that you will need implementations of BLAS levels 1-3.) | The first thing you must have on your system is a BLAS implementation. "BLAS" stands for "Basic Linear Algebra Subroutines," and is a standard interface for operations like matrix multiplication. It is designed as a building-block for other linear-algebra applications, and is used both directly by our code and in LAPACK (see below). By using it, we can take advantage of many highly-optimized implementations of these operations that have been written to the BLAS interface. (Note that you will need implementations of BLAS levels 1-3.) | ||

- | You can find more BLAS information, as well as a basic implementation, on the [http://www.netlib.org/blas/ BLAS Homepage]. Once you get things working with the basic BLAS implementation, it might be a good idea to try and find a more optimized BLAS code for your hardware. Vendor-optimized BLAS implementations are available as part of the Compaq CXML, IBM ESSL, SGI sgimath, and other libraries. Recently, there has also been work on self-optimizing BLAS implementations that can achieve performance competitive with vendor-tuned codes; see the [http://math-atlas.sourceforge.net/ ATLAS] homepage (and also [http://www.icsi.berkeley.edu/~bilmes/phipac/ PhiPACK]). Links to more BLAS implementations can be found on [http://SAL.KachinaTech.COM/B/0/BLAS.html SAL]. I recommend ATLAS, but it does take some time to compile. | + | You can find more BLAS information, as well as a basic implementation, on the [http://www.netlib.org/blas/ BLAS Homepage]. Once you get things working with the basic BLAS implementation, it might be a good idea to try and find a more optimized BLAS code for your hardware. Vendor-optimized BLAS implementations are available as part of the Intel MKL, HP CXML, IBM ESSL, SGI sgimath, and other libraries. An excellent, high-performance, free-software BLAS implementation is [http://xianyi.github.com/OpenBLAS/ OpenBLAS]; another is [http://math-atlas.sourceforge.net/ ATLAS]. |

Note that the generic BLAS does not come with a <code>Makefile</code><nowiki>; compile it with something like: </nowiki> | Note that the generic BLAS does not come with a <code>Makefile</code><nowiki>; compile it with something like: </nowiki> | ||

- | mkdir blas && cd blas # the BLAS archive does not create its own directory | ||

''get http://www.netlib.org/blas/blas.tgz'' | ''get http://www.netlib.org/blas/blas.tgz'' | ||

gunzip blas.tgz | gunzip blas.tgz | ||

tar xf blas.tar | tar xf blas.tar | ||

+ | cd BLAS | ||

f77 -c -O3 *.f # compile all of the .f files to produce .o files | f77 -c -O3 *.f # compile all of the .f files to produce .o files | ||

ar rv libblas.a *.o # combine the .o files into a library | ar rv libblas.a *.o # combine the .o files into a library | ||

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=== LAPACK === | === LAPACK === | ||

- | LAPACK, the Linear Algebra PACKage, is a standard collection of routines, built on BLAS, for more-complicated (dense) linear algebra operations like matrix inversion and diagonalization. You can download LAPACK from the [http://www.netlib.org/lapack/ LAPACK Home Page]. More LAPACK links can be found on [http://SAL.KachinaTech.COM/B/0/LAPACK.html SAL]. | + | LAPACK, the Linear Algebra PACKage, is a standard collection of routines, built on BLAS, for more-complicated (dense) linear algebra operations like matrix inversion and diagonalization. You can download LAPACK from the [http://www.netlib.org/lapack/ LAPACK Home Page]. |

- | Note that MPB looks for LAPACK by linking with <code>-llapack</code>. This means that the library must be called <code>liblapack.a</code> and be installed in a standard directory like <code>/usr/local/lib</code> (alternatively, you can specify another directory via the <code>LDFLAGS</code> environment variable as described earlier). (See also below for the <code>--with-lapack=''lib''</code> option to MPB's <code>configure</code> script, to manually specify a library location.) | + | Note that our software looks for LAPACK by linking with <code>-llapack</code>. This means that the library must be called <code>liblapack.a</code> and be installed in a standard directory like <code>/usr/local/lib</code> (alternatively, you can specify another directory via the <code>LDFLAGS</code> environment variable as described earlier). (See also below for the <code>--with-lapack=''lib''</code> option to our <code>configure</code> script, to manually specify a library location.) |

+ | |||

+ | I currently recommend installing [http://xianyi.github.com/OpenBLAS/ OpenBLAS], which includes LAPACK so you do not need to install it separately. |

## Current revision

### BLAS

The first thing you must have on your system is a BLAS implementation. "BLAS" stands for "Basic Linear Algebra Subroutines," and is a standard interface for operations like matrix multiplication. It is designed as a building-block for other linear-algebra applications, and is used both directly by our code and in LAPACK (see below). By using it, we can take advantage of many highly-optimized implementations of these operations that have been written to the BLAS interface. (Note that you will need implementations of BLAS levels 1-3.)

You can find more BLAS information, as well as a basic implementation, on the BLAS Homepage. Once you get things working with the basic BLAS implementation, it might be a good idea to try and find a more optimized BLAS code for your hardware. Vendor-optimized BLAS implementations are available as part of the Intel MKL, HP CXML, IBM ESSL, SGI sgimath, and other libraries. An excellent, high-performance, free-software BLAS implementation is OpenBLAS; another is ATLAS.

Note that the generic BLAS does not come with a `Makefile`

; compile it with something like:

get http://www.netlib.org/blas/blas.tgzgunzip blas.tgz tar xf blas.tar cd BLAS f77 -c -O3 *.f # compile all of the .f files to produce .o files ar rv libblas.a *.o # combine the .o files into a library su -c "cp libblas.a /usr/local/lib" # switch to root and install

(Replace `-O3`

with your favorite optimization options. On Linux, I use `g77 -O3 -fomit-frame-pointer -funroll-loops`

, with `-malign-double -mcpu=i686`

on a Pentium II.) Note that MPB looks for the standard BLAS library with `-lblas`

, so the library file should be called `libblas.a`

and reside in a standard directory like `/usr/local/lib`

. (See also below for the `--with-blas=`

option to MPB's *lib*`configure`

script, to manually specify a library location.)

### LAPACK

LAPACK, the Linear Algebra PACKage, is a standard collection of routines, built on BLAS, for more-complicated (dense) linear algebra operations like matrix inversion and diagonalization. You can download LAPACK from the LAPACK Home Page.

Note that our software looks for LAPACK by linking with `-llapack`

. This means that the library must be called `liblapack.a`

and be installed in a standard directory like `/usr/local/lib`

(alternatively, you can specify another directory via the `LDFLAGS`

environment variable as described earlier). (See also below for the `--with-lapack=`

option to our *lib*`configure`

script, to manually specify a library location.)

I currently recommend installing OpenBLAS, which includes LAPACK so you do not need to install it separately.