TensorFlow to Cloud FPGAs: Tradeoffs for Accelerating Deep Neural Networks
Stefan Hadjis, Kunle Olukotun · 2019
We present the first open-source TensorFlow to FPGA tool capable of running state-of-the-art DNNs. Running TensorFlow on the Amazon cloud FPGA instances, we provide competitive performance and higher accuracy compared to a proprietary tool, thus providing a public framework for research exploration in the DNN inference space. We also detail the optimizations needed to map modern DNN frameworks to FPGAs, provide novel analysis of design tradeoffs for FPGA DNN accelerators and present experiments across a range of DNNs.