Showing 13 open source projects for "blas"

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  • 1
    OpenBLAS

    OpenBLAS

    Optimized BLAS library based on GotoBLAS2 1.13 BSD version

    OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version. The BLAS (Basic Linear Algebra Subprograms) are routines that provide standard building blocks for performing basic vector and matrix operations. The Level 1 BLAS performs scalar, vector and vector-vector operations, the Level 2 BLAS performs matrix-vector operations, and the Level 3 BLAS performs matrix-matrix operations.
    Downloads: 8 This Week
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  • 2
    Peroxide

    Peroxide

    Rust numeric library with high performance and friendly syntax

    Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. For users familiar with numerical computing libraries like NumPy, MATLAB, or R, Rust's syntax might seem unfamiliar at first. This can make it more challenging to learn and use Rust libraries that heavily rely on Rust's unique features and syntax.
    Downloads: 0 This Week
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  • 3
    AppleAccelerate.jl

    AppleAccelerate.jl

    Julia interface to the macOS Accelerate framework

    Julia interface to the macOS Accelerate framework. This provides a Julia interface to some of the macOS Accelerate frameworks. At the moment, this package provides access to Accelerate BLAS and LAPACK using the libblastrampoline framework, an interface to the array-oriented functions, which provide a vectorized form for many common mathematical functions. The performance is significantly better than using standard libm functions in some cases, though there does appear to be some reduced accuracy.
    Downloads: 0 This Week
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  • 4
    Faiss

    Faiss

    Library for efficient similarity search and clustering dense vectors

    Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It...
    Downloads: 7 This Week
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  • 5
    Grenade

    Grenade

    Deep Learning in Haskell

    Grenade is a composable, dependently typed, practical, and fast recurrent neural network library for concise and precise specifications of complex networks in Haskell. Because the types are so rich, there's no specific term level code required to construct this network; although it is of course possible and easy to construct and deconstruct the networks and layers explicitly oneself. Networks in Grenade can be thought of as a heterogeneous list of layers, where their type includes not only...
    Downloads: 0 This Week
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  • 6

    Template Matrix/Vector Library for C++

    A fast, intuitive linear algebra library for C++.

    TMV is a comprehensive linear algebra library which uses operator overloading, views & delayed evaluation to simplify matrix and vector expressions in C++. It is well documented and can optionally call optimized BLAS/LAPACK for faster execution times
    Downloads: 0 This Week
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  • 7

    ViennaCL

    Linear algebra and solver library using CUDA, OpenCL, and OpenMP

    ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects.
    Downloads: 11 This Week
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  • 8
    CVM C++ Class Library encapsulates concepts of vector and square, band, symmetric and hermitian matrices in Euclidean space of real and complex numbers. It utilizes BLAS and LAPACK Fortran libraries. See http://cvmlib.com for binaries and more details.
    Downloads: 0 This Week
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  • 9
    The goal of the Fortran-to-Java project is to provide Java Application Programming Interfaces (APIs) to numerical libraries originally written in Fortran (particularly BLAS and LAPACK). The result of this work, JLAPACK, is distributed here.
    Downloads: 5 This Week
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  • 10
    QVision: Computer Vision Library for Qt

    QVision: Computer Vision Library for Qt

    Computer vision and image processing library for Qt.

    This library contains among other things a set of graphical widgets for video output, performance evaluation and augmented reality. The library also provides classes for several data types usually required by computer vision and image processing applications such as vectors, matrices, quaternions and images. Thanks to a large number of wrapper functions these objects can be used with highly efficient functionality from third party libraries such as OpenCV, GNU Scientific Library,...
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    Downloads: 0 This Week
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  • 11
    FLENS (Flexible Library for Efficient Numerical Solutions) is a C++ library for scientific computing. It can be considered as a very convenient and --- at the same time --- extremely efficient interface for BLAS and LAPACK. But it is much more than this
    Downloads: 0 This Week
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  • 12

    NTmatrix C++ Matrix Class

    A C++ matrix class for easy matrix manipulation

    A C++ matrix class for creating matrix objects and easily performing elementary operations between matrix objects including addition, subtraction, multiplication, transposition, and trace.
    Downloads: 0 This Week
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  • 13
    Tsunami Programming Language
    Tsunami is an open-source high performance computing language. With it you can write streaming data-parallel algorithms that utilize GPGPUs for orders-of-magnitude speed-up with the ease of writing sequential algorithms.
    Downloads: 0 This Week
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