Combining optimizations in automated low power design

Starting from sequential programs, we present an approach combining data reuse, multi-level MapReduce, and pipelining to automatically find the most power-efficient designs that meet speed and area constraints in the design space on Field-Programmable Gate Arrays (FPGAs). This combined approach enables trade-offs in power, speed and area: we show 63% reduction in power can be achieved with 27% increase in execution time. Compared to the sequential designs, our approach yields designs with up to 158 times reduction in execution time. Moreover, for a given execution time, our combined approach generates designs using up to 1.4 times less power than those produced by the same optimizations applied separately and can also find solutions missed by separating the optimizations.