Scalability Analysis of the Multi-Look Time Domain Processor on XSEDE Compute Resources

Without doubt the analysis of data from Polar Regions is an important aspect of identifying environmental impact by humans. The calculation of automatic techniques for determining ice and snow layer boundaries in radar echograms remains a hard problem because of two reasons. First, the data volume and the associated calculations to retrieve results are large requiring considerable supercomputing time. Second, the data itself provides challenges based on the high degree of noise, the often faint layer boundaries, and confusing linear structures caused by signal reflections and clutter. Thus it is necessary to optimize existing and future algorithms while improving the performance, but also introduce new techniques that combine together weak image cues, reasoning explicitly about uncertainty in both the evidence and the resulting layer boundary estimates. In this paper we report on two important findings. First the performance improvement of the Multi-look time processor program, and second the introduction of a new analysis technique improving our image analysis.