Showing 3 open source projects for "cpu usage"

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    PowerInfer

    PowerInfer

    High-speed Large Language Model Serving for Local Deployment

    PowerInfer is a high-performance inference engine designed to run large language models efficiently on personal computers equipped with consumer-grade GPUs. The project focuses on improving the performance of local AI inference by optimizing how neural network computations are distributed between CPU and GPU resources. Its architecture exploits the observation that only a subset of neurons in large models are frequently activated, allowing the system to preload frequently used neurons into...
    Downloads: 0 This Week
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  • 2
    GPU Hot

    GPU Hot

    Real-time NVIDIA GPU dashboard

    GPU Hot is an open-source, lightweight monitoring dashboard designed to provide real-time visibility into NVIDIA GPU performance across single machines or entire clusters. The project offers a self-hosted web interface that streams hardware metrics directly from GPU servers, enabling developers, ML engineers, and system administrators to observe GPU utilization and system behavior in real time through a browser. The dashboard collects and displays a wide range of performance metrics...
    Downloads: 8 This Week
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  • 3
    gpu_poor

    gpu_poor

    Calculate token/s & GPU memory requirement for any LLM

    gpu_poor is an open-source tool designed to help developers determine whether their hardware is capable of running a specific large language model and to estimate the performance they can expect from it. The project focuses on calculating GPU memory requirements and predicted inference speed for different models, hardware configurations, and quantization strategies. By analyzing factors such as model size, context length, batch size, and GPU specifications, the system estimates how much VRAM...
    Downloads: 0 This Week
    Last Update:
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