The impact of vectorization and parallelization of the slope algorithm on performance and energy efficiency on multi-core architecture

Calculation of land-surface parameters (e.g. slope, aspect, curvature) is an important part of many geospatial analyses. Current research trends are aimed at developing new software techniques to achieve the best performance and energy trade-off. In our work, we concentrate on the vectorization and parallelization to improve overall energy efficiency and performance of the neighborhood raster algorithms for the computation of land-surface parameters. We chose the slope calculation algorithm as the basis for our investigation. The parallelization was achieved through redesigning the the original sequential code with OpenMP SIMD vectorization hints for compiler, OpenMP loop parallelization, and the hybrid of these techniques. To evaluate both performance and energy savings, we tested our vector-parallel implementations on a multi-core computer for various data sizes. RAPL interface was used to measure energy consumption. The results showed that optimization towards high performance can also be an effective strategy for improving energy efficiency.