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.
Info
Conference Paper, 2020
UN SDG Classification
DK Main Research Area
Science/Technology
