Artificial Intelligence and Machine Learning on the network’s edge require workload-efficient computing at the lowest power and thermal headroom for operation in constrained environments. For this application, mid-range density FPGAs are an excellent option for implementing designs. The challenge is how to deploy scalable and extensible neural networks and how to enable software engineers with FPGA-based AI solutions performing efficient inferencing.
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