consumption. However, lowering the frequency of a CPU might increase the
execution time of an application running on that processor. Therefore, the
frequency that gives the best trade-off between the energy consumption and the
-performance of an application must be selected.\\
-In this paper, a new online frequencies selecting algorithm for heterogeneous
-platforms is presented. It selects the frequency which tries to give the best
+performance of an application must be selected.
+
+In this paper, a new online frequency selecting algorithm for heterogeneous
+platforms is presented. It selects the frequencies and tries to give the best
trade-off between energy saving and performance degradation, for each node
computing the message passing iterative application. The algorithm has a small
overhead and works without training or profiling. It uses a new energy model for
Figure~\ref{fig:st_freq}, the nodes are sorted by their computing power in
ascending order and the frequencies of the faster nodes are scaled down
according to the computed initial frequency scaling factors. The resulting new
-frequencies are colored in blue in Figure~\ref{fig:st_freq}. This set of
+frequencies are highlighted in Figure~\ref{fig:st_freq}. This set of
frequencies can be considered as a higher bound for the search space of the
optimal vector of frequencies because selecting frequency scaling factors higher
than the higher bound will not improve the performance of the application and it
