Showing 5 open source projects for "cpu high monitor"

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  • 1
    ncnn

    ncnn

    High-performance neural network inference framework for mobile

    ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs.
    Downloads: 25 This Week
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  • 2

    Halide

    A language for fast, portable data-parallel computation

    Halide is a programming language for fast, portable data-parallel computation. It was designed to make writing high-performance image and array processing code much easier on modern machines. It works on all major operating systems and with several CPU architectures (X86, ARM, MIPS, Hexagon, PowerPC) and GPU Compute APIs (CUDA, OpenCL, OpenGL, among others). It isn't a standalone programming language however; rather it is embedded in C++ which means that you write C++ code, building an in-memory representation of a Halide pipeline using Halide's C++ API. ...
    Downloads: 0 This Week
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  • 3
    ObjectBox

    ObjectBox

    Flutter database for super-fast Dart object persistence

    ObjectBox Flutter database is a great option for storing Dart objects in your cross-platform apps. Minimal CPU, memory and battery use make it an ideal choice for mobile and IoT devices. Made for efficient data access, the ObjectBox Flutter database is 10x faster than any alternative. See the performance benchmarks below. No need to learn SQL, as our NoSQL database uses a pure Dart API that is easy to work with and can be integrated in minutes. Plus: We built a data synchronization solution...
    Downloads: 1 This Week
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  • 4
    pipeless

    pipeless

    A computer vision framework to create and deploy apps in minutes

    ...You can easily use industry-standard models, such as YOLO, or load your custom model in one of the supported inference runtimes. Pipeless ships some of the most popular inference runtimes, such as the ONNX Runtime, allowing you to run inference with high performance on CPU or GPU out-of-the-box. You can deploy your Pipeless application with a single command to edge and IoT devices or the cloud.
    Downloads: 0 This Week
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    MongoDB Atlas runs apps anywhere

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  • 5
    LLDebugTool

    LLDebugTool

    LLDebugTool is a debugging tool for developers and testers

    LLDebugTool is a powerful in-app debugging tool for iOS that provides detailed insights into app performance, logs, network requests, and crash data. It offers a floating window for developers to monitor the app in real-time without external tools.
    Downloads: 0 This Week
    Last Update:
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