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Hardware Acceleration · Awesome GitHub Repositories

7 repos

Awesome GitHub RepositoriesHardware Acceleration

Drivers and libraries that offload intensive computational tasks to specialized hardware like GPUs or AI accelerators.

Explore 7 awesome GitHub repositories matching operating systems & systems programming · Hardware Acceleration. Refine with filters or upvote what's useful.

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  3. Hardware Interfacing and Drivers
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Awesome Hardware Acceleration GitHub Repositories

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  • PaddlePaddle/PaddleOCR

    PaddlePaddle/PaddleOCR

    70,931GitHubView on GitHub↗

    PaddleOCR is a comprehensive optical character recognition framework designed for detecting and transcribing text from images and documents into structured, machine-readable formats. It provides a modular computer vision pipeline that decouples image preprocessing, text detection, and character recognition into indepen

    Pythonai4sciencechineseocrdocument-parsing
  • vllm-project/vllm

    vllm-project/vllm

    70,745GitHubView on GitHub↗

    vLLM is a high-throughput inference engine designed for the efficient serving and execution of large language models. It functions as a production-ready distributed model server, providing standard API protocols for online serving while also supporting offline batch processing. The system is built to maximize token gen

    Pythonamdblackwellcuda
  • OpenHands/OpenHands

    OpenHands/OpenHands

    67,974GitHubView on GitHub↗

    OpenHands is an autonomous agent framework designed for software engineering workflows. It provides a modular platform for orchestrating AI agents that reason, plan, and execute tasks within isolated, containerized development environments. By integrating with standard version control and development tools, the system

    Pythonagentartificial-intelligencechatgpt
  • keras-team/keras

    keras-team/keras

    63,858GitHubView on GitHub↗

    Keras is a high-level deep learning framework designed for constructing and training neural networks through the composition of modular, functional layers. It serves as a comprehensive modeling toolkit that provides standardized procedures for defining, evaluating, and deploying complex architectures. By utilizing a di

    Pythondata-sciencedeep-learningjax
  • FFmpeg/FFmpeg

    FFmpeg/FFmpeg

    57,281GitHubView on GitHub↗

    FFmpeg is a cross-platform framework and multimedia processing suite designed for the manipulation, transcoding, and streaming of audio and video data. It functions as a comprehensive collection of command-line tools and low-level libraries that provide high-performance encoding and decoding capabilities for a wide ran

    Caudiocffmpeg
  • ultralytics/yolov5

    ultralytics/yolov5

    56,830GitHubView on GitHub↗

    YOLOv5 is a comprehensive computer vision framework designed for end-to-end deep learning, specializing in real-time object detection, image classification, and instance segmentation. It provides a unified toolkit that manages the entire lifecycle of a model, from initial dataset configuration and hyperparameter tuning

    Pythoncoremldeep-learningios
  • deepfakes/faceswap

    deepfakes/faceswap

    54,974GitHubView on GitHub↗

    Faceswap is a comprehensive framework for automated media manipulation and neural face synthesis. It provides a modular pipeline that manages the entire lifecycle of facial feature extraction, deep learning model training, and image conversion. By coordinating complex computer vision workflows, the system enables users

    Pythondeep-face-swapdeep-learningdeep-neural-networks

Explore sub-tags

  • Cross-Platform AI AcceleratorsOptimizations that enable generative models to run efficiently across various hardware architectures.
  • Device SelectionSelecting hardware devices for computation.
  • GPU AccelerationMethods and configurations for offloading compute-intensive tasks to graphics processing units to improve performance.
  • Inference Acceleration DriversConfiguration interfaces for mapping inference workloads to specific hardware-level acceleration libraries.
  • Inference AcceleratorsTools and formats for optimizing model execution on dedicated hardware units like GPUs or NPUs.
  • Media Hardware AcceleratorsFrameworks for utilizing GPU or dedicated video hardware for encoding and decoding.