Showing 10 open source projects for "gpu hardware"

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  • 1
    Starling Framework

    Starling Framework

    2D GPU-accelerated framework for ActionScript developers

    Starling is an open-source 2D framework for ActionScript developers that leverages GPU acceleration via Adobe's Stage3D API to create smooth, high-performance games and applications across desktop and mobile platforms. It mimics the traditional Flash display list while dramatically improving performance, making it a popular choice for Flash developers transitioning into more efficient, hardware-accelerated environments.
    Downloads: 0 This Week
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  • 2
    bitnet.cpp

    bitnet.cpp

    Official inference framework for 1-bit LLMs

    bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous...
    Downloads: 7 This Week
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  • 3
    tvm

    tvm

    Open deep learning compiler stack for cpu, gpu, etc.

    Apache TVM is an open source machine learning compiler framework for CPUs, GPUs, and machine learning accelerators. It aims to enable machine learning engineers to optimize and run computations efficiently on any hardware backend. The vision of the Apache TVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging...
    Downloads: 0 This Week
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  • 4
    Unsloth-MLX

    Unsloth-MLX

    Bringing the Unsloth experience to Mac users via Apple's MLX framework

    ...This project removes traditional barriers that prevent Mac users from prototyping and experimenting with LLM training locally by allowing the same code used in cloud GPU environments to run on M-series hardware, improving workflow continuity and reducing iteration costs. It supports loading and training Hugging Face models with fine-tuning strategies like SFT, DPO, ORPO, and GRPO and even handles exporting models to formats like GGUF for downstream use, although some limitations apply with quantized models. ...
    Downloads: 1 This Week
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  • 5
    MegEngine

    MegEngine

    Easy-to-use deep learning framework with 3 key features

    MegEngine is a fast, scalable and easy-to-use deep learning framework with 3 key features. You can represent quantization/dynamic shape/image pre-processing and even derivation in one model. After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR...
    Downloads: 4 This Week
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  • 6
    QtAV

    QtAV

    A multimedia framework based on Qt and FFmpeg

    QtAV is a cross-platform and high performance multimedia playback framework based on Qt and FFmpeg. Features: timeline preview, gpu decoding etc
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    Downloads: 33 This Week
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  • 7
    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 on Mac directly through Metal. ...
    Downloads: 0 This Week
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  • 8
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    ...The gpu backend is selected by default, so the above command is equivalent to if a compatible GPU resource is found on the system. The Intel Math Kernel Library takes advantages of the parallelization and vectorization capabilities of Intel Xeon and Xeon Phi systems. When hyperthreading is enabled on the system, we recommend the following KMP_AFFINITY setting to make sure parallel threads are 1:1 mapped to the available physical cores.
    Downloads: 0 This Week
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  • 9
    ND2D

    ND2D

    A Flash Molehill (Stage3D) GPU accelerated 2D game engine

    ND2D is a 2D game framework for Flash that uses Stage3D / Molehill (i.e. the GPU acceleration in newer Flash Player versions). It allows game developers to build 2D games with lots of sprites, leveraging GPU for better performance. It includes display tree constructs, sprite sheets, particle systems, cameras, post-processing etc., made to simplify building high-performance 2D content in Flash. ND2D was built to make an ease use of hardware accelerated 2D content in the Flashplayer. ...
    Downloads: 0 This Week
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  • 10
    jQuery Transit

    jQuery Transit

    Super-smooth CSS3 transformations and transitions for jQuery

    jQuery Transit is a classic jQuery plugin that brought ergonomic, chainable CSS3 transitions and transforms to web apps before modern animation APIs were commonplace. It exposes a simple .transition() method so you can animate transforms, opacity, colors, and other CSS properties with minimal code. Under the hood, it leans on GPU-accelerated CSS transforms where available, falling back gracefully, which made complex motion feel smooth even on modest devices. The plugin abstracts away vendor...
    Downloads: 0 This Week
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