Multidimensional data visualization is one of the primary foundations supporting data
analysis used for understanding the hidden relationships between items and dimensions of …

Visualizing graphs and networks in non‐Euclidean space can have benefits such as natural
focus+ context in hyperbolic space and the familiarity of interactions in spherical space …

Torus networks are an attractive topology in supercomputing, balancing the tradeoff
between network diameter and hardware costs. The nodes in a torus network are connected …

By skeptics and undecided we refer to nodes in clustered social networks that cannot be
assigned easily to any of the clusters. Such nodes are typically found either at the interface …

The overall efficiency of an extreme-scale supercomputer largely relies on the performance
of its network interconnects. Several of the state of the art supercomputers use networks …

We design and implement La VALSE—a scalable visualization tool to explore tens of
millions of records of reliability, availability, and serviceability (RAS) logs—for IBM Blue …

Chord diagrams are a popular high-dimensional method for showing connections between
nodes, however they have scalability limitations and lack advanced methods for interaction …

Current and future supercomputers have tens of thousands of compute nodes
interconnected with high-dimensional networks and complex network topologies for …

In practical applications, the data set we deal with is typically high dimensional, which not
only affects training speed but also makes it difficult for people to analyze and understand. It …

Visualization design studies bring together visualization researchers and domain experts to
address yet unsolved data analysis challenges stemming from the needs of the domain …