FPGA加速调研

普遍量化使用DoReFa Net量化的方法

在模型上大多是AlexNet, VGG16, ShuffleNetV2

  • TensorFlow to cloud FPGAs: Tradeoffs for accelerating deep neural networks

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  • FPGA-based training accelerator utilizing sparseness of convolutional neural network

    SPARSE CNN TRAINING ACCELERATOR

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  • A high-performance CNN processor based on FPGA for mobilenets

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  • RNA: An accurate residual network accelerator for quantized and reconstructed deep neural networks

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  • Synetgy: Algorithm-hardware Co-design for ConvNet accelerators on embedded FPGAS

使用改进的ShuffleNets V2，用移位代替乘法

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Last modification：May 19, 2021
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恰饭环节