Reducing the Power Consumption of Matrix Multiplications by Vectorization
Thomas Jakobs, Michael Hofmann, Gudula Rünger · 2016
The power consumption of programs and algorithms is currently a very active research field. This includes the investigation of the effect of different programming techniques on power consumption. Some programming techniques have already been studied intensively. However, there are techniques that did not get as much attention as needed so far. One of these techniques is the vectorization of programs, which uses special operations to calculate several data in one step. In this article, we investigate the effect of vectorization on the power consumption and study several program versions of dense matrix multiplication which combine vectorization with other techniques, such as loop unrolling or compiler options. We show that the use of vectorization is not only capable of improving the performance but can also reduce the power and energy consumption of programs.