Approximated Canonical Signed Digit for Error Resilient Intelligent Computation

Abstract

Lowering the energy consumption in applications operating on large datasets is one of the main challenges in modern computing. In this context, it is especially important to lower the energy required to transfer data from/to the memory. Usually, this is obtained by applying smart encoding techniques to the data. In this work, we show how to reduce the switching activity in buses and floating-point units by an approximated canonical signed-digit encoder. The precision of the encoding is programmable and can be chosen depending on the application’s required accuracy.