Showing 2 open source projects for "standalone"

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    XNNPACK

    XNNPACK

    High-efficiency floating-point neural network inference operators

    XNNPACK is a highly optimized, low-level neural network inference library developed by Google for accelerating deep learning workloads across a variety of hardware architectures, including ARM, x86, WebAssembly, and RISC-V. Rather than serving as a standalone ML framework, XNNPACK provides high-performance computational primitives—such as convolutions, pooling, activation functions, and arithmetic operations—that are integrated into higher-level frameworks like TensorFlow Lite, PyTorch Mobile, ONNX Runtime, TensorFlow.js, and MediaPipe. The library is written in C/C++ and designed for maximum portability, efficiency, and performance, leveraging platform-specific instruction sets (e.g., NEON, AVX, SIMD) for optimized execution. ...
    Downloads: 3 This Week
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    Cmockery

    Cmockery

    A lightweight library to simplify and generalize writing unit tests

    Cmockery is a lightweight unit testing framework for the C programming language, designed to make writing and executing C tests simple and portable. It allows developers to test the logic of C modules in isolation by replacing external dependencies with mock functions. Cmockery focuses on testing functionality rather than environment-specific behavior, making it ideal for projects where code must run on diverse or constrained systems. Unlike many modern frameworks, Cmockery is compatible...
    Downloads: 0 This Week
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