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NAME

       LAPACK - library of linear algebra routines

什麼是 LAPACK ?

    LAPACK 是一個 Fortran 77 子程式的 transportable library , 用來解決多數數字線性代數中共同的問題: systems of
    linear equations, linear least squares problems, eigenvalue problems, 還有 singular value problems.   它在大
    部分現代的高效能計算機中可以高效地運作。

    LAPACKLINPACKEISPACK 的後繼者。 它擴充套件了這些庫的功能,包含了線性系統的 equilibration, iterative
    refinement,  error  bounds,  和  driver  routines,  routines  for  computing  and  re-ordering  the   Schur
    factorization,  還有  condition  estimation  routines  for  eigenvalue  problems.   LAPACK 透過包含 finding
    singular values and eigenvalues of bidiagonal and tridiagonal matrices respectively that arise  in  SVD  and
    symmetric  eigenvalue  problems  的高精度演算法提高了  EISPACK 中標準演算法的精度。 這些演算法和軟體被重新編
    寫,在向量處理器上,高效能 ``superscalar'' 工作站上和 共享記憶體的多處理器上都可以獲得高效率。 LAPACK 軟體還
    附帶了一個複雜的測試和時間測算套件。

如何得到 LAPACK

    完整的  LAPACK 軟體包可以從 xnetlib 和 NAG 得到,也可以從 netlib 獲得特定的庫。 要檢視 LAPACK 內容的描述,向
    netlib@ornl.gov 發一封訊息型別為: send index from lapack 的電子郵件。

    Xnetlib is an X-version of netlib recently developed at the University of Tennessee and Oak  Ridge  National
    Laboratory.   Unlike  netlib,  which  uses  electronic mail to process requests for software and other text,
    xnetlib uses an X Window graphical user interface and a socket-based connection between the  user's  machine
    and the xnetlib server machine to process software requests. The complete contents of LAPACK is available in
    tar/compress format from xnetlib.

    To receive a copy of xnetlib send the message "send xnetlib.shar from xnetlib" to netlib@ornl.gov.

    When you receive the shar file, remove the mail header, save it to a file, type 'sh filename' and follow the
    instructions in the README file.

    Alternatively, the complete LAPACK package can be obtained from NAG on magnetic media for a handling charge.
    For further details contact NAG at one of the following addresses:

    NAG Inc                         NAG Ltd              NAG GmbH
    1400 Opus Place               Wilkinson House      Schleissheimerstrasse 5
    Suite 200                     Jordan Hill Road     W-8046 Garching bei Munchen
    Downers Grove, IL 60515-5702  Oxford OX2 8DR       Germany
    USA                           England
    Tel: +1 708 971 2337          Tel: +44 865 511245  Tel: +49 89 3207395
    Fax: +1 708 971 2706          Fax: +44 865 310139  Fax: +49 89 3207396

    LAPACK has been thoroughly tested, on many different types of computers.  The LAPACK  project  supports  the
    package  in  the  sense  that  reports  of errors or poor performance will gain immediate attention from the
    developers. Such reports, descriptions of interesting applications, and other comments  should  be  sent  by
    electronic mail to lapack@cs.utk.edu.

LAPACK USERS' GUIDE

    The LAPACK Users' Guide is published by SIAM and was made available May, 1992.  LAPACK Users' Guide gives an
    informal introduction to the design of the algorithms and software, summarizes the contents of the  package,
    and  describes  the conventions used in the software and documentation, and includes complete specifications
    for calling the routines.  The LAPACK Users' Guide can be purchased from: SIAM; 3600 University City Science
    Center;  Philadelphia,  PA  19104-2688;  215-382-9800,  FAX  215-386-7999.   It  will also be available from
    booksellers.  The Guide costs $15.60 for SIAM members, and $19.50 for  non-members.   Please  specify  order
    code OT31 when ordering.  To order by email, send email to service@siam.org.

    A  list  of  known  problems,  bugs, and compiler errors for LAPACK, as well as errata for the LAPACK Users'
    Guide and the LAPACK code itself, is maintained on netlib.  For  a  copy  of  this  report,  send  email  to
    netlib@ornl.gov with a message of the form: send release_notes from lapack.

LAPACK WORKING NOTES

    A  number  of  working  notes  were written during the development of LAPACK and published as LAPACK Working
    Notes, initially by Argonne National Laboratory and later by the University of  Tennessee.   Many  of  these
    reports  have  subsequently  appeared  as  journal  articles.   Most of these working notes are available in
    postscript form from netlib.  To receive a list of available reports, send email to netlib@ornl.gov  with  a
    message  of  the  form: send index from lapack/lawns.  Otherwise, requests for copies of these working notes
    can be sent to the following address.

    LAPACK Project c/o J.J. Dongarra Computer Science Department University of  Tennessee  Knoxville,  Tennessee
    37996-1301 USA Email: lapack@cs.utk.edu

ACKNOWLEDGEMENTS

    LAPACK  has  been  funded  in  part  by  NSF, DOE, and DARPA, with developmental support from NAG Ltd., Cray
    Research, and many friends and colleagues around the world.

    Ed Anderson, Zhao-jun Bai, Chris Bischof, Jim Demmel, Jack Dongarra, Jeremy Du Croz,  Anne  Greenbaum,  Sven
    Hammarling, Alan McKenney, Susan Ostrouchov, and Danny Sorensen

                 (           l    l    l    l )
                 (           a   -a    a   -a )
           1/4 * ( p    p             -p   -p )
                 ( a   -a             -a    a )
                 ( c    c   -c   -c           )
                 ( k   -k   -k    k           )

NAMING SCHEME

    The  name  of  each LAPACK routine is a coded specification of its function (within the very tight limits of
    standard Fortran 77 6-character names).

    All driver and computational routines have names of the form XYYZZZ, where for some driver routines the  6th
    character is blank.

    The first letter, X, indicates the data type as follows:

          S  REAL
          D  DOUBLE PRECISION
          C  COMPLEX
          Z  COMPLEX*16  or DOUBLE COMPLEX

    The  next  two  letters, YY, indicate the type of matrix (or of the most significant matrix).  Most of these
    two-letter codes apply to both real and complex matrices; a few apply specifically to one or the other.

    The last three letters ZZZ indicate the computation performed.  For example, SGEBRD is  a  single  precision
    routine that performs a bidiagonal reduction (BRD) of a real general matrix.

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