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| + | == 메타데이터 == | ||
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| + | ===위키데이터=== | ||
| + | * ID : [https://www.wikidata.org/wiki/Q642141 Q642141] | ||
2020년 12월 26일 (토) 06:04 판
노트
- LAPACK is a collection of high-performance linear algebra routines written in FORTRAN and built on top of BLAS.[1]
- Many vendors supply an optimised version of the LAPACK and BLAS libraries.[2]
- However, there is a large learning curve to using LAPACK.[3]
- Many scientific libraries also use LAPACK underneath.[3]
- To that end, I've provided a small working example written in C++ using LAPACK to get you started.[3]
- update port to slave port of math/lapack, and updated to 3.5.0 accordingly.[4]
- LAPACK is a FORTRAN program system for solving linear equations for matrices which fit entirely in core.[5]
- LAPACK has been very extensively tested on a wide variety of machines and is written completely in Standard FORTRAN 77.[5]
- The *gegv family of routines have been removed from LAPACK 3.6.0 and have been deprecated in SciPy 0.17.0.[6]
- The classical numerical linear algebra libraries, BLAS and LAPACK, play an important role in the scientific computing field.[7]
- CBLAS and LAPACKE are thin wrappers around BLAS and LAPACK respectively, providing the C API / ABI.[7]
- For system level library switching, two custom eselect modules (eselect-blas, eselect-lapack) are provided.[7]
- A: Simply reinstall the virtual packages and your favorite BLAS/LAPACK providers with the eselect-ldso flag toggled.[7]
- Before installing the Haskell bindings you need to install the BLAS and LAPACK packages.[8]
- However, the pkg-config files for LAPACK seem to be installed in a non-standard location.[8]
- The property of a unit diagonal is preserved by some operations and enables some optimizations by LAPACK.[8]
- LAPACK is intended for dense and banded matrices, but not general sparse matrices.[9]
- Most users will already have LAPACK available, either a version they have installed themselves or a vendor version.[9]
- It is assumed that you already downloaded LAPACK from the netlib repository at lapack.tgz.[10]
- A final note: On 64-bit targets, LAPACK cannot be built using GCC 2.95.2 without specifying the -femulate-complex flag.[10]
- This talk outlines the computational package called LAPACK.[11]
- The reference implementation for BLAS/LAPACK is written in Fortran and is very low performance.[12]
- A highly optimized implementation of LAPACK is available on all OSC clusters as part of the Intel Math Kernel Library (MKL).[13]
- We recommend that you use MKL rather than building LAPACK for yourself.[13]
소스
- ↑ Department of Physics
- ↑ Using LAPACK from C
- ↑ 3.0 3.1 3.2 How to start using LAPACK in c++?
- ↑ FreshPorts -- math/lapack: Library of Fortran 77 subroutines for linear algebra
- ↑ 5.0 5.1 lapack.html
- ↑ Low-level LAPACK functions (scipy.linalg.lapack) — SciPy v1.5.4 Reference Guide
- ↑ 7.0 7.1 7.2 7.3 Blas-lapack-switch
- ↑ 8.0 8.1 8.2 lapack: Numerical Linear Algebra using LAPACK
- ↑ 9.0 9.1 LAPACK Example Programs
- ↑ 10.0 10.1 LAPACK build and test guide
- ↑ LAPACK: A Linear Algebra Library for High-Performance Computers
- ↑ BLAS/LAPACK at TACC
- ↑ 13.0 13.1 Ohio Supercomputer Center
메타데이터
위키데이터
- ID : Q642141