Showing 4 open source projects for "portable python 3.8"

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  • 1
    NSync

    NSync

    nsync is a C library that exports various synchronization primitives

    nsync is a portable C library that provides a collection of advanced synchronization primitives designed to facilitate safe and efficient multithreaded programming. It offers reader-writer locks, condition variables, run-once initialization, waitable counters, and waitable bits for coordination and cancellation between threads. Unlike traditional pthreads-based synchronization, nsync introduces conditional critical sections, allowing developers to wait for arbitrary conditions without explicit...
    Downloads: 8 This Week
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  • 2
    CPU Features

    CPU Features

    A cross platform C99 library to get cpu features at runtime

    ..., and s390x—and works on major operating systems like Linux, macOS, Windows, FreeBSD, Android, and iOS. Implemented in portable C99, it is thread-safe, has no memory allocations, and raises no exceptions, making it suitable even for use in low-level system libraries. The design emphasizes portability, extensibility, and compatibility with sandboxed or restricted environments where direct CPU access may be limited.
    Downloads: 0 This Week
    Last Update:
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  • 3
    DocFetcher

    DocFetcher

    Desktop search application

    DocFetcher is an Open Source desktop search application: It allows you to search the contents of files on your computer. — You can think of it as Google for your local files. The application runs on Windows, Linux and Mac OS X.
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    Downloads: 2,345 This Week
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  • 4
    TensorFlow MacOS

    TensorFlow MacOS

    TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute

    This repository provided a pre-release of TensorFlow and TensorFlow Addons tailored for macOS 11+ with native hardware acceleration via Apple’s ML Compute, supporting both Apple Silicon (M1) and Intel Macs. It shipped ready-made Python 3.8 wheels and install scripts so developers could quickly get an accelerated stack running without building from source. As TensorFlow added a Metal PluggableDevice path, the project directed users toward using Apple’s tensorflow-metal to get GPU acceleration...
    Downloads: 0 This Week
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