copy and paste this google map to your website or blog!
Press copy button and paste into your blog or website.
(Please switch to 'HTML' mode when posting into your blog. Examples: WordPress Example, Blogger Example)
BLAS (Basic Linear Algebra Subprograms) The Level 1 BLAS perform scalar, vector and vector-vector operations, the Level 2 BLAS perform matrix-vector operations, and the Level 3 BLAS perform matrix-matrix operations Because the BLAS are efficient, portable, and widely available, they are commonly used in the development of high quality linear algebra software, LAPACK for example
LAPACK — Linear Algebra PACKage LAPACK routines are written so that as much as possible of the computation is performed by calls to the Basic Linear Algebra Subprograms (BLAS) LAPACK is 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
What is the relation between BLAS, LAPACK and ATLAS BLAS is a collection of low-level matrix and vector arithmetic operations (“multiply a vector by a scalar”, “multiply two matrices and add to a third matrix”, etc ) LAPACK is a collection of higher-level linear algebra operations Things like matrix factorizations (LU, LLt, QR, SVD, Schur, etc) that are used to do things like “find the eigenvalues of a matrix”, or “find the
How does BLAS get such extreme performance? - Stack Overflow Only the reference implementation of BLAS is implemented in Fortran However, all these BLAS implementations provide a Fortran interface such that it can be linked against LAPACK (LAPACK gains all its performance from BLAS) Optimized compilers play a minor role in this respect (and for GotoBLAS OpenBLAS the compiler does not matter at all)
Sparse BLAS - Netlib Sparse BLAS In the spirit of the dense BLAS, work is underway in the BLAS Technical Forum to establish a standard for the sparse BLAS The sparse BLAS interface addresses computational routines for unstructured sparse matrices Sparse BLAS also contains the three levels of operations as in the dense case
What is a good free (open source) BLAS LAPACK library for . net (C#)? Since the program is mainly a prototype created to confirm a theory, a C# implementation will suffice (compared to a possibly speedier C++ one), but I would still like a good BLAS or LAPACK library available to save me some coding Long story short, can anybody recommend a free open source BLAS or LAPACK library for use with net? Best regards
XBLAS - Extra Precise Basic Linear Algebra Subroutines - Netlib EXTENDED PRECISION is only used internally; the input and output arguments remain the same as in the existing BLAS At present, we only allow Single, Double, or Extra internal precision Extra precision is implemented as double-double precision (128-bit total, 106-bit significand) The routines for the double-double precision basic arithmetic operations +, -, *, were developed by David Bailey
blas - Use cmake FindBLAS to link OpenBLAS - Stack Overflow I am using cmake 3 16, and I know that cmake supports finding OpenBLAS by using FindBLAS (here) I am trying to link OpenBLAS to my c++ project Here is my CMakeLists txt cmake_minimum_required(
LAPACK: dgemm - Netlib 188 * 189 * -- Reference BLAS level3 routine -- 190 * -- Reference BLAS is a software package provided by Univ of Tennessee, --