LAPACK LAPACK provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. The associated matrix factorizations (LU, Cholesky, QR, SVD, Schur, generalized Schur) are also provided, as are related computations such as reordering of the Schur factorizations and estimating condition numbers. Dense and banded matrices are handled, but not general sparse matrices. In all areas, similar functionality is provided for real and complex matrices, in both single and double precision. The original goal of the LAPACK project was to make the widely used EISPACK and LINPACK libraries (in Netlib) run efficiently on shared-memory vector and parallel processors. On these machines, LINPACK and EISPACK are inefficient because their memory access patterns disregard the multi-layered memory hierarchies of the machines, thereby spending too much time moving data instead of doing useful floating-point operations. LAPACK addresses this problem by reorganizing the algorithms to use block matrix operations, such as matrix multiplication, in the innermost loops. These block operations can be optimized for each architecture to account for the memory hierarchy, and so provide a transportable way to achieve high efficiency on diverse modern machines. We use the term "transportable" instead of "portable" because, for fastest possible performance, LAPACK requires that highly optimized block matrix operations be already implemented on each machine. LAPACK routines are written so that as much as possible of the computation is performed by calls to the Basic Linear Algebra Subprograms (BLAS). While LINPACK and EISPACK are based on the vector operation kernels of the Level 1 BLAS, LAPACK was designed at the outset to exploit the Level 3 BLAS -- a set of specifications for Fortran subprograms that do various types of matrix multiplication and the solution of triangular systems with multiple right-hand sides. Because of the coarse granularity of the Level 3 BLAS operations, their use promotes high efficiency on many high-performance computers, particularly if specially coded implementations are provided by the manufacturer. Highly efficient machine-specific implementations of the BLAS are available for many modern high-performance computers. The BLAS enable LAPACK routines to achieve high performance with transportable software.

Current Version:   3.0 License Type:   Free

Home Site: http://www.netlib.org/lapack/ Source Code Availability: Yes Available Binary Packages: Debian Package:   Yes, http://www.debian.org/distrib/packages RedHat RPM Package:   Yes, ftp://ftp.redhat.com/redhat/contrib Other Packages:   Yes, prebuilt LAPACK libraries are available on netlib for a variety of architectures, see Home Site. Though Linux binary is not there, you could look at LAPACK and BLAS Libraries for Linux (LAPACK version 2.0 though) and Dynamically Loadable LAPACK items in SAL. Targeted Platforms: PCs, workstations, include g77/Linux compiling script Software/Hardware Requirements: BLAS (The Fortran 77 reference implementation of the BLAS is provided with the LAPACK distribution in case an optimized version of the BLAS is not available.)

Other Links: http://www.netlib.org/lapack/lug/lapack_lug.html (On-Line LAPACK Users' Guide) Mailing Lists/USENET News Groups: lapack@cs.utk.edu for questions and comments. User Comments: Some commercial numerical libraries such as NAG F77 library and some commercial compilers such as PGI compiling system come with compiled BLAS and LAPACK. See A Screen Shot? (Not Yet)

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