Scalable Contour Tree Computation by Data Parallel Peak Pruning.

As data sets grow to exascale, automated data analysis and visualization are increasingly important, to intermediate human understanding and to reduce demands on disk storage via in situ analysis. Trends in architecture of high performance computing systems necessitate analysis algorithms to make effective use of combinations of massively multicore and distributed systems. One of the principal analytic tools is the contour tree, which analyses relationships between contours to identify features of more than local importance.

Verifying scientific simulations via comparative and quantitative visualization.

This article presents a visualization-assisted process that verifies scientific-simulation codes. Code verification is necessary because scientists require accurate predictions to interpret data confidently. This verification process integrates iterative hypothesis verification with comparative, feature, and quantitative visualization.