Showing 7 open source projects for "libusb-1.0"

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  • 1
    NLPModels.jl

    NLPModels.jl

    Data Structures for Optimization Models

    This package provides general guidelines to represent non-linear programming (NLP) problems in Julia and a standardized API to evaluate the functions and their derivatives. The main objective is to be able to rely on that API when designing optimization solvers in Julia.
    Downloads: 0 This Week
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  • 2
    OpenCL.jl

    OpenCL.jl

    OpenCL Julia bindings

    Julia interface for the OpenCL parallel computation API. This package aims to be a complete solution for OpenCL programming in Julia, similar in scope to PyOpenCL for Python. It provides a high level API for OpenCL to make programing hardware accelerators, such as GPUs, FPGAs, and DSPs, as well as multicore CPUs much less onerous.
    Downloads: 1 This Week
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  • 3
    JavaCall.jl

    JavaCall.jl

    Call Java from Julia

    Call Java programs from Julia. Julia 1.3.0 through Julia 1.6.2 are tested and guaranteed to work on Linux, macOS, and Windows via continuous integration. Julia 1.6.2 and newer should work on Linux and Windows. The JULIA_COPY_STACKS environment variable should be set to 1 on macOS and Linux, but not Windows.
    Downloads: 0 This Week
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  • 4
    Arrow Julia

    Arrow Julia

    Official Julia implementation of Apache Arrow

    This is a pure Julia implementation of the Apache Arrow data standard. This package provides Julia AbstractVector objects for referencing data that conforms to the Arrow standard. This allows users to seamlessly interface Arrow formatted data with a great deal of existing Julia code.
    Downloads: 0 This Week
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  • 5
    FFTW.jl

    FFTW.jl

    Julia bindings to the FFTW library for fast Fourier transforms

    This package provides Julia bindings to the FFTW library for fast Fourier transforms (FFTs), as well as functionality useful for signal processing. These functions were formerly a part of Base Julia. Users with a build of Julia based on Intel's Math Kernel Library (MKL) can use MKL for FFTs by setting a preference in their top-level project by either using the FFTW.set_provider!() method, or by directly setting the preference using Preferences.jl. Note that this choice will be recorded for...
    Downloads: 0 This Week
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  • 6
    CuArrays.jl

    CuArrays.jl

    A Curious Cumulation of CUDA Cuisine

    CuArrays provides a fully-functional GPU array, which can give significant speedups over normal arrays without code changes. CuArrays are implemented fully in Julia, making the implementation elegant and extremely generic.
    Downloads: 0 This Week
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  • 7
    Merlin.jl

    Merlin.jl

    Deep Learning for Julia

    Merlin is a deep learning framework written in Julia. It aims to provide a fast, flexible and compact deep learning library for machine learning. Merlin is tested against Julia 1.0 on Linux, OS X, and Windows (x64).
    Downloads: 0 This Week
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