67 citations · 67 across the 1 of their papers we have counts for
2 papers
eess.SP2019★ 67 cited
AddNet: Deep Neural Networks Using FPGA-Optimized Multipliers
Julian Faraone, Martin Kumm, Martin Hardieck +4
Low-precision arithmetic operations to accelerate deep-learning applications on field-programmable gate arrays (FPGAs) have been studied extensively, because they offer the potenti…
eess.SP2019
Unrolling Ternary Neural Networks
Stephen Tridgell, Martin Kumm, Martin Hardieck +4
The computational complexity of neural networks for large scale or real-time applications necessitates hardware acceleration. Most approaches assume that the network architecture a…