diff --git a/docs/about.md b/docs/about.md index 4069bd80e1..d9cb584b35 100644 --- a/docs/about.md +++ b/docs/about.md @@ -2,15 +2,10 @@ drawing -FINN is an -experimental framework from Xilinx Research Labs 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. -It is not -intended to be a generic DNN accelerator like xDNN, but rather a tool for -exploring the design space of DNN inference accelerators on FPGAs. +FINN is an ML framework by the Integrated Communications and AI Lab of AMD Research & Advanced Development. +It provides an end-to-end flow for the exploration and implementation of quantized neural network inference solutions on FPGAs. +FINN generates dataflow architectures as a physical representation of the implemented custom network in space. +It is not a generic DNN acceleration solution but relies on co-design and design space exploration for quantization and parallelization tuning so as to optimize a solutions with respect to resource and performance requirements.
## Features @@ -31,16 +26,16 @@ design space. ## Who are we? -The FINN team consists of members of AMD Research under Ivo Bolsens (CTO) and members of CommsDC Solutions Engineering under Allen Chen (AECG-CommsDCSolnEng), working very closely with the Pynq team and Kristof Denolf and Jack Lo for integration with video processing. +The FINN team consists of members of AMD Research under Ralph Wittig (AMD Research & Advanced Development) and members of Custom & Strategic Engineering under Allen Chen, working very closely with the Pynq team. -The FINN Team (CTO) +The FINN Team (AMD Research and Advanced Development) From top left to bottom right: Yaman Umuroglu, Michaela Blott, Alessandro Pappalardo, Lucian Petrica, Nicholas Fraser, Thomas Preusser, Jakoba Petri-Koenig, Ken O’Brien -The FINN Team (CommsDC Solutions Engineering) +The FINN Team (Custom & Strategic Engineering) -From top left to bottom right: Eamonn Dunbar, Kasper Feurer, Aziz Bahri, Fionn O'Donohoe, Mirza Mrahorovic +From top left to bottom right: Eamonn Dunbar, Kasper Feurer, Aziz Bahri, John Monks, Mirza Mrahorovic diff --git a/docs/img/finn-stack.PNG b/docs/img/finn-stack.PNG new file mode 100755 index 0000000000..961232c4bf Binary files /dev/null and b/docs/img/finn-stack.PNG differ diff --git a/docs/img/finn-stack.png b/docs/img/finn-stack.png deleted file mode 100644 index e34b1ecb45..0000000000 Binary files a/docs/img/finn-stack.png and /dev/null differ diff --git a/docs/img/finn-team1.png b/docs/img/finn-team1.png index 774d8e8ee9..c311720ba8 100755 Binary files a/docs/img/finn-team1.png and b/docs/img/finn-team1.png differ diff --git a/docs/index.md b/docs/index.md index 35b5f68742..5066c5cf9e 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,18 +1,13 @@ # FINN -drawing +drawing -FINN is an -experimental framework from Xilinx Research Labs 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. -It is not -intended to be a generic DNN accelerator offering like [Vitis AI](https://www.xilinx.com/products/design-tools/vitis/vitis-ai.html), but rather a tool for -exploring the design space of DNN inference accelerators on FPGAs. -

-A new, more modular version of the FINN compiler is currently under development on GitHub, and we welcome contributions from the community! +FINN is a machine learning framework by the Integrated Communications and AI Lab of AMD Research & Advanced Development. +It provides an end-to-end flow for the exploration and implementation of quantized neural network inference solutions on FPGAs. +FINN generates dataflow architectures as a physical representation of the implemented custom network in space. +It is not a generic DNN acceleration solution but relies on co-design and design space exploration for quantization and parallelization tuning so as to optimize a solutions with respect to resource and performance requirements. +

+The FINN compiler is under active development on GitHub, and we welcome contributions from the community! ## Quickstart