Towards energy efficiency and maximum computational intensity for stencil algorithms using wavefront diamond temporal blocking

Abstract: We study the impact of tunable parameters on computational intensity (i.e., inverse code balance) and energy consumption of multicore-optimized wavefront diamond temporal blocking (MWD) applied to different stencil-based update schemes. MWD combines the concepts of diamond tiling and multicore-aware wavefront blocking in order to achieve lower cache size requirements than standard single-core wavefront temporal blocking. We analyze the impact of the cache block size on the theoretical and observed code balance, introduce loop tiling in the leading dimension to widen the range of applicable diamond sizes, and show performance results on a contemporary Intel CPU. The impact of code balance on power dissipation on the CPU and in the DRAM is investigated and shows that DRAM power is a decisive factor for energy consumption, which is strongly influenced by the code balance. Furthermore we show that highest performance does not necessarily lead to lowest energy even if the clock speed is fixed.