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  • Informatics Colloquium 25.2. Energy-efficient neural networks for embedded systems

    Informatics Colloquium 25.2. 2019, 14:00 lecture hall D2 Ing. Vojtěch Mrázek, Ph.D., FIT VUT Energy-efficient neural networks for embedded systems Abstract: Artificial neural networks are optimized for high-performance computer systems. However, the inference path of the NNs is often executed in small embedded systems such as special ASIC or FPGA accelerators. Since these systems are typically battery-powered, the energy consumption becomes crucial. In this context, this talk deals with three topics. (i) Overview and challenges of hardware NN accelerators. (ii) Error resiliency of neural networks. (iii) Approximations of NN inference path for applications such as low power image classifiers.
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