Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
State-of-the-art wearable devices such as embedded biomedical monitoring systems apply voltage scaling to lower as much as possible their energy consumption and achieve longer battery lifetimes. While embedded memories often rely on Error Correction Codes (ECC) for error protection, in this paper we explore how the characteristics of biomedical applications can be exploited to develop new techniques with lower power overhead. We then introduce the Dynamic eRror compEnsation And Masking (DREAM) technique, that provides partial memory protection with less area and power overheads than ECC. Different tradeoffs between the error correction ability of the techniques and their energy consumption are examined to conclude that, when properly applied, DREAM consumes 21% less energy than a traditional ECC with Single Error Correction and Double Error Detection (SEC/DED) capabilities.
Devis Tuia, Diego Michael Schibli
David Atienza Alonso, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola, Una Pale, Rodrigo Mariño Andrés