// doc/matrixwrap.dox

// Copyright 2009-2011 Microsoft Corporation Arnab Ghoshal

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namespace kaldi {

/** \page matrixwrap External matrix libraries

Here we describe how our \ref matrix "matrix library" makes use of

external libraries.

\section matrixwrap_summary Overview

The matrix code in Kaldi is mostly a wrapper on top of the

linear-algebra libraries BLAS and LAPACK. The code has been designed to be as flexible

as possible in terms of what libraries it can use. Currently it supports four options:

- ATLAS, which is an implementation of BLAS plus a subset of LAPACK (with a different interface)

- Some implementation of BLAS plus CLAPACK (note: this has not been tested recently).

- Intel's MKL, which provides both BLAS and LAPACK

- OpenBLAS, which provides BLAS and LAPACK

The code has to "know" which of these four options is being used, because although in principle

BLAS and LAPACK are standardized, there are some differences in the interfaces.

The Kaldi code requires exactly one

of the three strings HAVE_ATLAS, HAVE_CLAPACK, HAVE_OPENBLAS or HAVE_MKL to be defined

(e.g. using -DHAVE_ATLAS as an option to the compiler). It must then be

linked with the appropriate libraries. The code that deals most directly

with including the external libraries and setting up the appropriate

typedef's and defines, is in \ref kaldi-blas.h. However, the rest of

the matrix code is not completely insulated from these issues because the ATLAS

and CLAPACK versions of higher-level routines are called differently (so

we have a lot of "#ifdef HAVE_ATLAS" directives and the like). Additionally, some routines

are not even available in ATLAS so we have had to implement them ourselves.

The "configure" script in the "src" directory is responsible for setting up Kaldi to use the libraries.

It does this by creating the file "kaldi.mk" in the "src" directory, which gives appropriate flags

to the compiler. If called with no arguments it will use any ATLAS installation it can find in "normal" places

in your system, but it is quite configurable. See the script itself for usage.

\section matrixwrap_blas Basic Linear Algebra Subroutines (BLAS)

Because we refer a lot to BLAS in this section, we briefly explain what it is.

BLAS is a set of subroutine declarations that correspond to low-level

matrix-vector operations. There is Level 1 Blas (vector-vector), Level 2

(vector-matrix) and Level 3 (matrix-matrix). They have names like daxpy (for

double-precision a*x plus y), and dgemm (for double general matrix-matrix

multiply). BLAS has various actual implementations. The "reference BLAS",

supplied I believe by Netlib (the folks who also brought us the most common version

of LAPACK), is one. ATLAS is another one (but it also implements some functions

from LAPACK).

\section matrixwrap_lapack Linear Algebra PACKage (LAPACK)

Lapack is a set of linear-algebra routines, originally written in Fortran. It includes

higher-level routines than BLAS, such as matrix inversion, SVD, etc.

Netlib has implemented this (this is the "normal" LAPACK). LAPACK requires

BLAS. It is possible to mix-and-match LAPACK and BLAS implementations

(e.g. Netlib's LAPACK with ATLAS's BLAS).

CLAPACK is a version of LAPACK that has been converted from Fortan to C automatically

using the f2c utility. When we talk about using LAPACK, we are actually

talking about using CLAPACK. Because CLAPACK has been converted to C using the

f2c utility, when we link against it we need to include the f2c library (e.g. -lf2c,

or -lg2c if using recent versions of gcc), otherwise we will get linking errors.

\section matrixwrap_atlas Automatically Tuned Linear Algebra Software (ATLAS)

ATLAS is a well known implementation of BLAS plus a subset of LAPACK. The

general idea of ATLAS is to tune to the particular processor setup, so the

compilation process is quite complex and can take a while. For this reason,

it can be quite tricky to compile ATLAS. On UNIX-based systems, you can't even do it unless you

are root or are friendly with your system administrator, because to compile

it you need to turn off CPU throttling; and on Windows, ATLAS does not compile

"natively", only in Cygwin. Sometimes it can be a better bet to find libraries that

have been compiled by someone else for your particular platform, but we can't offer

much advice on how to do this. ATLAS generally performs better

than the "reference BLAS" available from Netlib. ATLAS only includes

a few LAPACK routines. These include matrix inversion and Cholesky factorization,

but not SVD. For this reason we have implemented a couple more of the LAPACK

routines (SVD and eigenvalue decomposition); see

the next section.

ATLAS conforms to the BLAS interface, but its interface for the subset of

LAPACK routines that it provides is not the same as Netlib's (it's more

C-like and less FORTRAN-ish). For this reason, there are quite a number of #ifdef's in our code

to switch between the calling styles, depending whether we are

linking with ATLAS or CLAPACK.

\subsection matrixwrap_atlas_install_windows Installing ATLAS (on Windows)

For instructions on how to install ATLAS on Windows (and note that these

instructions require Cygwin), see the file windows/INSTALL.atlas

in our source distribution. Note that our Windows setup is not being

actvely maintained at the moment and we don't anticipate that it will work

very cleanly.

\subsection matrixwrap_atlas_install_linux Installing ATLAS (on Linux)

If your system does not have ATLAS installed, or there are no pre-built binaries

available, you will need to install ATLAS from source. Even if your system has

pre-built binaries available, they may not be the best binaries possible for your

architecture so it is probably a better idea to compile from source.

The easiest way to do this

is to cd from "src" to "../tools" and to run ./install_atlas.sh.

If this does not work, the detailed installation

instructions can be found at: http://math-atlas.sourceforge.net/atlas_install/.

One useful note is that before installing ATLAS you should turn off CPU

throttling using "cpufreq-selector -g performance" (cpufreq-selector may be in

sbin), if it is enabled (see the ATLAS install page). You can first try running the

"install_atlas.sh" script before doing this, to see whether it works-- if CPU

throttling is enabled, the ATLAS installation scripts will die with an error.

\section matrixwrap_mkl Intel Math Kernel Library (MKL)

Intel MKL also provides C-language interface to the BLAS and LAPACK routines,

and can be used with Kaldi by using the -DHAVE_MKL compiler flag. The linker

flags for MKL tend to be quite different depending on the OS, architecture,

compiler, etc. used. We have tested Kaldi on 32-bit Windows and x86_64 (or EMT64) Linux.

Flags for other platforms can be obtained from:

http://software.intel.com/en-us/articles/intel-mkl-link-line-advisor/

\section matrixwrap_openblas OpenBLAS

Kaldi now supports linking against the OpenBLAS library, which is an implementation

of BLAS and parts of LAPACK. OpenBLAS also automatically compiles Netlib's implementation of LAPACK,

so that it can explort LAPACK in its entirety.

OpenBLAS is a fork of the GotoBLAS project (an assembler-heavy implementation of BLAS) which is no longer being

maintained. In order to use GotoBLAS you can cd from "src" to "../tools", type

"make openblas", then cd to "../src" and give the correct option to the "configure" script

to use OpenBLAS (look at the comments at the top of the configure script to find this option).

Thanks to Sola Aina for suggesting this and helping us to get this to work.

\section matrixwrap_jama Java Matrix Package (JAMA)

JAMA is an implementation of linear-algebra routines for Java, written

in collaboration between NIST and MathWorks and put into the public domain

(see math.nist.gov/javanumerics/jama). We used some of this code to fill

in a couple of holes in ATLAS-- specifically, if we're compiling with

-DHAVE_ATLAS, we don't have the CLAPACK routines for SVD and eigenvalue

decomposition available, so we use code from JAMA that we translated into

C++. See the EigenvalueDecomposition class, and the function MatrixBase::JamaSvd.

The user of the matrix library should never have to interact with this code

directly.

\section matrixwrap_linking_errors Linking errors you might encounter

To make sure the matrix library is compiling correctly, type "make" in the matrix/

directory and see if it succeeds. A lot of compilation issues will manifest themselves

as linking errors. In this section we give a summary of some of the more common

linking errors (at least, those that relate specifically to the matrix library).

Depending on the compilation option (-DHAVE_CLAPACK, -DHAVE_LAPACK or -DHAVE_MKL),

the code will be expecting to link with different things. When debugging linking

errors, bear in mind that the problem could be a mismatch between the compilation

options and the libraries that you actually linked.

\subsection matrix_err_f2c f2c or g2c errors

The f2c library is often required if you link with CLAPACK, because it

was created with f2c and that tool requires you to link with its own library.

Not that with recent versions of gcc you have to link with -lg2c not -lf2c.

The symbols that will be missing if this is the problem, include:

s_cat, pow_dd, r_sign, pow_ri, pow_di, s_copy, s_cmp, d_sign

\subsection matrix_err_clapack CLAPACK linking errors

You will get these errors if you compiled with -DHAVE_CLAPACK but did

not provide the CLAPACK library. The symbols you will be missing are:

sgetrf_, sgetri_, dgesvd_, ssptrf_, ssptri_, dsptrf_, dsptri_, stptri_, dtptri_

This will usually be called something like liblapack.a or if using a

dynamic library, you would

type -llapack. Be careful-- this has the same name as the ATLAS-supplied

library "lapack" (see section \ref matrix_err_clapack),

but it supplies different symbols. The native CLAPACK version of liblapack

has symbols like those above (e.g. sgesvd_, sgetrf_), but the ATLAS version

has symbols like clapack_sgetrf and also ones like ATL_sgetrf.

\subsection matrix_err_blas BLAS linking errors

You will get these errors if you failed to link against an implementation

of BLAS. These errors can also occur if libraries are linked in the wrong

order. CLAPACK requires BLAS, so you have to link BLAS after CLAPACK.

The symbols you will see if you failed to link with BLAS include:

cblas_sger, cblas_saxpy, cblas_dapy, cblas_ddot, cblas_sdot, cblas_sgemm, cblas_dgemm

To fix these, link with a static library like libcblas.a, or do -lcblas (assuming

such a library is on your LD_LIBRARY_PATH). This library may come from ATLAS (which

is preferable), or from Netlib (the "reference BLAS"). To the best of my current

knowledge they have the same interface.

\subsection matrix_err_cblaswrap cblaswrap linking errors

CLAPACK seems to rely on symbols like f2c_sgemm that are some kind of wrapping

of symbols like cblas_sgemm and so on. I'm not sure exactly what is being

wrapped, and why. Anyway, the effect is that you may need to include a library

named libcblaswr.a or dynamically using -lcblaswr, if you are using Netlib's

CLAPACK. The cblaswrap library should be invoked before the cblas one. If you

are missing cblaswrap, you will see errors about symbols like:

f2c_sgemm, f2c_strsm, f2c_sswap, f2c_scopy, f2c_sspmv, f2c_sdot, f2c_sgemv

and so on (there are a lot of these symbols).

\subsection matrix_err_atl_blas Missing the ATLAS implementation of BLAS

If you linked with an ATLAS implementation of BLAS but only did -lcblas (or compiled

with libcblas.a), but did not do -latlas (or compile with libatlas.a), you will have

a problem because ATLAS's BLAS routines like cblas_sger internally call things that are

in libatlas. If you have this problem you will have undefined references like:

ATL_dgemm, ATL_dsyrk, ATL_dsymm, ATL_daxpy, ATL_ddot, ATL_saxpy, ATL_dgemv, ATL_sgemv

\subsection matrix_err_atl_clapack Missing the ATLAS implementation of (parts of) CLAPACK

These errors can only occur if you compiled wiht the -DHAVE_ATLAS option.

Atlas's name for the CLAPACK routines are different from clapack's own (they

have clapack_ prepended to indicate the origin, which can be quite confusing).

If you have undefined references to the following symbols:

clapack_sgetrf, clapack_sgetri, clapack_dgetrf, clapack_dgetri

then it means you failed to link with an ATLAS library containing these symbols.

This may be variously called liblapack.a, libclapack.a or liblapack_atlas.a,

but you can tell that it is the right one if it defines a symbol called ATL_cgetrf

(type "nm <library-name> | grep ATL_cgetrf" to see). You may be able to link

dynamically with this library using -llapack or some similar option.

Watch out, because a library called liblapack.a or liblapack.so could

be CLAPACK or it could be ATLAS's version of CLAPACK, and as noted in section

\ref matrix_err_f2c, they supply different symbols. The only way to find

out is to look inside it using "nm" or "strings".

*/

}