Towards Parameter-Based Profiling for MARE2DEM Performance Modeling.

The Controlled Source Electromagnetic (CSEM) combined with seismic surveys has been used to explore new oil and gas reservoirs. The MARE2DEM application generates as mesh that represents a resistivity model of the seafloor underground. From a set of electromagnetic readings, the application runs a data inversion (using Maxwell's equations) along many steps to converge to a resistivity model that more closely matches the measured data. This data inversion procedure is very compute-bound because of the large amount of arithmetic operations involved. As consequence, the MARE2DEM application divides the workload into smaller work grains, called refinement groups due to the usage of Adaptive Mesh Refinement (AMR). These groups are processed independently in a parallel fashion by a set of workers. It is known that parallel processing suffers from delays and resource underutilization if the load remains imbalanced. In this article, we propose an analysis of the performance and imbalance of the MARE2DEM through source code inspection and trace analysis. The novelty of our investigation consists in the usage of runtime parameters to more profoundly understand and characterize the refinement groups' execution time and variability. Our results show that the execution time of the refinement groups is strongly impacted by both the number of processed nodes present on the input mesh and the measured data associated to each refinement group.