Preface to the First Edition

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Preface to the First Edition

The development of LAPACK was a natural step after specifications of the Level 2 and 3 BLAS were drawn up in 1984-86 and 1987-88. Research on block algorithms had been ongoing for several years, but agreement on the BLAS made it possible to construct a new software package to take the place of LINPACK and EISPACK, which would achieve much greater efficiency on modern high-performance computers. This also seemed to be a good time to implement a number of algorithmic advances that had been made since LINPACK and EISPACK were written in the 1970's. The proposal for LAPACK was submitted while the Level 3 BLAS were still being developed and funding was obtained from the National Science Foundation (NSF) beginning in 1987.

LAPACK is more than just a more efficient update of its popular predecessors. It extends the functionality of LINPACK and EISPACK by including: driver routines for linear systems; equilibration, iterative refinement and error bounds for linear systems; routines for computing and re-ordering the Schur factorization; and condition estimation routines for eigenvalue problems. LAPACK improves on the accuracy of the standard algorithms in EISPACK by including high accuracy algorithms for finding singular values and eigenvalues of bidiagonal and tridiagonal matrices, respectively, that arise in SVD and symmetric eigenvalue problems.

We have tried to be consistent with our documentation and coding style throughout LAPACK in the hope that LAPACK will serve as a model for other software development efforts. In particular, we hope that LAPACK and this guide will be of value in the classroom. But above all, LAPACK has been designed to be used for serious computation, especially as a source of building blocks for larger applications.

The LAPACK project has been a research project on achieving good performance in a portable way over a large class of modern computers. This goal has been achieved, subject to the following qualifications. For optimal performance, it is necessary, first, that the BLAS are implemented efficiently on the target machine, and second, that a small number of tuning parameters (such as the block size) have been set to suitable values (reasonable default values are provided). Most of the LAPACK code is written in standard Fortran 77, but the double precision complex data type is not part of the standard, so we have had to make some assumptions about the names of intrinsic functions that do not hold on all machines (see section 6.1). Finally, our rigorous testing suite included test problems scaled at the extremes of the arithmetic range, which can vary greatly from machine to machine. On some machines, we have had to restrict the range more than on others.

Since most of the performance improvements in LAPACK come from restructuring the algorithms to use the Level 2 and 3 BLAS, we benefited greatly by having access from the early stages of the project to a complete set of BLAS developed for the CRAY machines by Cray Research. Later, the BLAS library developed by IBM for the IBM RISC/6000 was very helpful in proving the worth of block algorithms and LAPACK on ``super-scalar'' workstations. Many of our test sites, both computer vendors and research institutions, also worked on optimizing the BLAS and thus helped to get good performance from LAPACK. We are very pleased at the extent to which the user community has embraced the BLAS, not only for performance reasons, but also because we feel developing software around a core set of common routines like the BLAS is good software engineering practice.

A number of technical reports 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 later appeared as journal articles. Appendix E lists the LAPACK Working Notes, and the Bibliography gives the most recent published reference.

A follow-on project, LAPACK 2, has been funded in the U.S. by the NSF and DARPA. One of its aims will be to add a modest amount of additional functionality to the current LAPACK package - for example, routines for the generalized SVD and additional routines for generalized eigenproblems. These routines will be included in a future release of LAPACK when they are available. LAPACK 2 will also produce routines which implement LAPACK-type algorithms for distributed memory machines, routines which take special advantage of IEEE arithmetic, and versions of parts of LAPACK in C and Fortran 90. The precise form of these other software packages which will result from LAPACK 2 has not yet been decided.

As the successor to LINPACK and EISPACK, LAPACK has drawn heavily on both the software and documentation from those collections. The test and timing software for the Level 2 and 3 BLAS was used as a model for the LAPACK test and timing software, and in fact the LAPACK timing software includes the BLAS timing software as a subset. Formatting of the software and conversion from single to double precision was done using Toolpack/1 [66], which was indispensable to the project. We owe a great debt to our colleagues who have helped create the infrastructure of scientific computing on which LAPACK has been built.

The development of LAPACK was primarily supported by NSF grant ASC-8715728. Zhaojun Bai had partial support from DARPA grant F49620-87-C0065; Christian Bischof was supported by the Applied Mathematical Sciences subprogram of the Office of Energy Research, U.S. Department of Energy, under contract W-31-109-Eng-38; James Demmel had partial support from NSF grant DCR-8552474; and Jack Dongarra had partial support from the Applied Mathematical Sciences subprogram of the Office of Energy Research, U.S. Department of Energy, under Contract DE-AC05-84OR21400.

The cover was designed by Alan Edelman at UC Berkeley who discovered the matrix by performing Gaussian elimination on a certain 20-by-20 Hadamard matrix.

We acknowledge with gratitude the support which we have received from the following organizations, and the help of individual members of their staff: Cornell Theory Center; Cray Research Inc.; IBM ECSEC Rome; IBM Scientific Center, Bergen; NAG Ltd.

We also thank many, many people who have contributed code, criticism, ideas and encouragement. We wish especially to acknowledge the contributions of: Mario Arioli, Mir Assadullah, Jesse Barlow, Mel Ciment, Percy Deift, Augustin Dubrulle, Iain Duff, Alan Edelman, Victor Eijkhout, Sam Figueroa, Pat Gaffney, Nick Higham, Liz Jessup, Bo Kågström, Velvel Kahan, Linda Kaufman, L.-C. Li, Bob Manchek, Peter Mayes, Cleve Moler, Beresford Parlett, Mick Pont, Giuseppe Radicati, Tom Rowan, Pete Stewart, Peter Tang, Carlos Tomei, Charlie Van Loan, Kresimir Veselic, Phuong Vu, and Reed Wade.

Finally we thank all the test sites who received three preliminary distributions of LAPACK software and who ran an extensive series of test programs and timing programs for us; their efforts have influenced the final version of the package in numerous ways.

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