Transcription of FINN: A Framework for Fast, Scalable Binarized …
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FINN: A Framework for Fast, Scalable Binarized …
FINN: A Framework for fast , Scalable Binarized NeuralNetwork InferenceYaman Umuroglu* , Nicholas J. Fraser* , Giulio Gambardella*, Michaela Blott*,Philip Leong , Magnus Jahre and Kees Vissers**Xilinx Research Labs; Norwegian University of Science and Technology; University of has shown that convolutional neural networks con-tain significant redundancy, and high classification accuracycan be obtained even when weights and activations are re-duced from floating point to binary values. In this paper,we presentFinn, a Framework for building fast and flexibleFPGA accelerators using a flexible heterogeneous stream-ing architecture. By utilizing a novel set of optimizationsthat enable efficient mapping of Binarized neural networksto hardware, we implement fully connected, convolutionaland pooling layers, with per-layer compute resources beingtailored to user-provided throughput requirements.
FINN: A Framework for Fast, Scalable Binarized Neural Network Inference Yaman Umuroglu*†, Nicholas J. Fraser*‡, Giulio Gambardella*, Michaela Blott*, Philip Leong‡, Magnus Jahre† and Kees Vissers* *Xilinx Research Labs; †Norwegian University of Science and Technology; ‡University of Sydney yamanu@idi.ntnu.no ABSTRACT …
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