USB V3.1 Power Delivery Type-C Port Evaluation board for OTI9108 IP
Compact neural network engine offering scalable performance (32, 64, or 128 MACs) at very low energy footprints
The product architecture natively supports the most common network layers found in these applications including convolution, depth-wise separable convolution, fully connected, LSTM, pooling, reshaping, and concatenation layers. Other layers can be supported (and further accelerated using TIE) using the host Tensilica DSP. The NNE 110 provides performance scalability from 32 to 128 MACs for 8x8-bit MAC computation, suiting a variety of low-power AI needs. It offers unique features for AI enhancement including hardware-based sparsity for compute and bandwidth reduction as well as on the-fly weight decompression for smaller system footprints.
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