Finn

Dataflow compiler for QNN inference on FPGAs

Machine Learning Model TrainingML FrameworksOpen Source

About

FINN is an experimental framework from Integrated Communications and AI Lab of AMD Research & Advanced Development to explore deep neural network inference on FPGAs. It specifically targets quantized neural networks, with emphasis on generating dataflow-style architectures customized for each network. The resulting FPGA accelerators are highly efficient and can yield high throughput and low latency. The framework is fully open-source in order to give a higher degree of flexibility, and is intended to enable neural network research spanning several layers of the software/hardware abstraction stack.

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1,061
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307
License
BSD-3-Clause
Last commit
1 months ago
Python

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Vendor

Xilinx

Publisher of CHaiDNN, Vitis-AI and LogicNets

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