P. Sotiriadis

A Hybrid OR-MUX Lower-Part Approximate Adder for Energy-Efficient Edge AI Inference on FPGA

Approximate computing has become a prominent design paradigm for energy-constrained edge AI hardware, where relaxed arithmetic precision enables significant gains in speed, area, and power. This paper presents a novel $n$-bit Hybrid OR-MUX Lower-Part Approximate Adder (HOMAxA-1) that divides operands into an approximat...