Presenter

Reaching exascale computing, the negligible power consumption per transistor is considered important due to high integration. Therefore, this has gradually led to hardware aware scientific computing, which leverages not only the optimal usage of the hardware in terms of energy efficiency but also steers the future hardware development. In that context, my interests as PhD student comprise power consumption data acquisition, dedicated algorithms for characterizing the hardware as well as ML prediction models of hardware power consumption.