Synthesis of Power-Efficient Analog Neural Networks for Signal Processing

Conference: ANALOG 2020 - 17. ITG/GMM-Fachtagung
09/28/2020 - 09/30/2020 at online

Proceedings: ITG-Fb. 293 Analog 2020

Pages: 6Language: englishTyp: PDF

Authors:
Aul, Florian; Hedrich, Lars (Institute for Computer Science, Goethe University Frankfurt, Germany)
Katsaouni, Nikoletta; Schulz, Marcel H. (Institute for Cardiovascular Regeneration, Goethe University Frankfurt, Germany)

Abstract:
This paper presents a concept and an implementation for an automatic, power-aware synthesis of neural networks as analog circuits. Our concept incorporates fully automatic design space exploration (synthesis) of powerefficient neuron-building blocks. Further, it implements techniques to have a programmable, and at the same time small neural network. First results on the schematic level for energy consumption of a small neural network applied to a peak detection dataset are presented.