The Impact of CUDA Execution Configuration Parameters on the Performance and Energy of a Seismic Application

Simulating the propagation of acoustic waves is the basis of seismic imaging software, widely used by the industry for locating and detecting new oil basins. Due to their complexity, these simulations require a high computational processing power obtained using GPUs. To fully exploit these devices’ computing potential, it is necessary to rightly define the configuration of the number of blocks and threads per block that will be assigned to a given kernel. However, as we show in this paper, this task is challenging since the ideal configuration will vary according to the grid size and the target metric (e.g., performance or energy). In this scenario, this paper evaluates different execution configurations for the Fletcher method, a widely used seismic application. When evaluating sixteen different grid sizes over a distinct set of configurations, we show that rightly choosing the number of blocks and threads per block can deliver up to 2 times more performance and save 18% of energy consumption compared to the standard way the Fletcher method is implemented.