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- ATLAS
ATLAS (Automatically Tuned Linear Algebra Software)
provides C and Fortran77 interfaces to a portably efficient BLAS implementation,
as well as a few routines from LAPACK.
BLAS (Basic Linear Algebra Subprograms) consist of three level of routines. Level 1 is a collection of linear algebra subprograms to perform common linear algebra operations with vector operands. Level 2 is a collection of linear algebra subprograms to perform common linear algebra operations with matrix and vector operands. Level 3 is a collection of linear algebra subroutines to perform common linear algebra operations with matrix operands.
LAPACK (Linear Algebra PACKage) is written in Fortran77 and 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. In all areas, similar functionality is provided for real and complex matrices, in both single and double precision.
Location /usr/local/ATLAS/
- BLACS
BLACS (Basic Linear Algebra Communication Subprograms) project is an ongoing investigation whose purpose is to create a linear algebra oriented message passing interface that may be implemented efficiently and uniformly across a large range of distributed memory platforms. The length of time required to implement efficient distributed memory algorithms makes it impractical to rewrite programs for every new parallel machine. The BLACS exist in order to make linear algebra applications both easier to program and more portable. It is for this reason that the BLACS are used as the communication layer of ScaLAPACK.
Location /usr/local/BLACS/
- ScaLapack
ScaLAPACK is a library of high-performance linear algebra routines for distributed-memory message-passing MIMD computers and networks of workstations supporting PVM and/or MPI. This library includes a subset of LAPACK routines redesigned for distributed memory MIMD parallel computers. It is currently written in a Single-Program-Multiple-Data style using explicit message passing for interprocessor communication. Like LAPACK, the ScaLAPACK routines are based on block-partitioned algorithms in order to minimize the frequency of data movement between different levels of the memory hierarchy. The fundamental building blocks of the ScaLAPACK library are distributed memory versions (PBLAS) of the Level 1, 2 and 3 BLAS, and a set of Basic Linear Algebra Communication Subprograms (BLACS) for communication tasks that arise frequently in parallel linear algebra computations. In the ScaLAPACK routines, all interprocessor communication occurs within the PBLAS and the BLACS.
The library is currently written in Fortran 77 (with the exception of a few symmetric eigenproblem auxiliary routines written in C to exploit IEEE arithmetic) in a Single Program Multiple Data (SPMD) style using explicit message passing for interprocessor communication.
PBLAS (Parallel Basic Linear Algebra Subprograms) are a small core library of linear algebra utilities, which can be highly optimized for various parallel architectures. Software that relies on the PBLAS is thus highly portable, and will typically run very efficiently. In particular, the SCALAPACK parallel linear algebra libraries make extensive use of the PBLAS.
Location /usr/local/SCALAPACK/
- FFTW
FFTW (Fastest Fourier Transform in the West) is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data (as well as of even/odd data, i.e. the discrete cosine/sine transforms or DCT/DST).
Location /usr/local/FFTW/
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