Shypd.aiThe largest open index of AI toolsTinyEngine is an Open Source & Models tool that provides a memory-efficient neural network library for microcontrollers. It enables tiny deep learning on IoT devices by co-designing with TinyNAS to fit tight memory budgets.
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TinyEngine is the official implementation of a memory-efficient and high-performance neural network library specifically designed for Microcontrollers. As a core component of MCUNet, a system-algorithm co-design framework, TinyEngine works in conjunction with TinyNAS to facilitate tiny deep learning on IoT devices with extremely tight memory budgets. It significantly outperforms existing inference libraries like TF-Lite Micro, CMSIS-NN, and X-CUBE-AI by improving inference speed by 1.1-18.6x and reducing peak memory by 1.3-3.6x. Key optimization techniques include in-place depth-wise convolution, patch-based inference, operator fusion, SIMD programming, and various loop optimizations to enhance performance and minimize memory footprint.
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