The explosive growth in volume, velocity, and diversity of data produced by mobile devices
and cloud applications has contributed to the abundance of data or 'big data.'Available …

The most common abstraction used by visualization libraries and applications today is what
is known as the visualization pipeline. The visualization pipeline provides a mechanism to …

Visualization and analysis tools, techniques, and algorithms have undergone a rapid
evolution in recent decades to accommodate explosive growth in data size and complexity …

Visualizations are frequently used as a means to understand trends and gather insights from
datasets, but often take a long time to generate. In this paper, we focus on the problem of …

Petascale plasma physics simulations have recently entered the regime of simulating
trillions of particles. These unprecedented simulations generate massive amounts of data …

With the technical advances, the amount of big data is increasing day-by-day such that the
traditional software tools face a burden in handling them. Additionally, the presence of the …

Bit arrays, or bitmaps, are used to significantly speed up set operations in several areas,
such as data warehousing, information retrieval, and data mining, to cite a few. However …

Large scale data warehouses rely heavily on secondary indexes, such as bitmaps and b-
trees, to limit access to slow IO devices. However, with the advent of large main memory …

Modern scientific datasets present numerous data management and analysis challenges.
State-of-the-art index and query technologies are critical for facilitating interactive …

Data visualization is an effective mechanism for identifying trends, insights, and anomalies
in data. On large datasets, however, generating visualizations can take a long time, delaying …