Gonçalo Raposo

Positnn: Training Deep Neural Networks with Mixed Low-Precision Posit

Low-precision formats have proven to be an efficient way to reduce not only the memory footprint but also the hardware resources and power consumption of deep learning computations. Under this premise, the posit numerical format appears to be a highly viable substitute for the IEEE floating-point, b…