As we have entered an era of high resolution earth observation, the RS data are undergoing
an explosive growth. The proliferation of data also give rise to the increasing complexity of …

Weather forecasting plays a fundamental role in the early warning of weather impacts on
various aspects of human livelihood. For instance, weather forecasting provides decision …

An ultra-scalable fully-implicit solver is developed for stiff time-dependent problems arising
from the hyperbolic conservation laws in nonhydrostatic atmospheric dynamics. In the …

Clustering trajectory data is an important way to mine hidden information behind moving
object sampling data, such as understanding trends in movement patterns, gaining high …

Multiple-point geostatistical (MPS) simulation methods have attracted an enormous amount
of attention in earth and environmental sciences due to their ability to enhance extraction …

As the 2020 roadblock approaches, the need of breakthrough in computing systems has
directed researchers to novel computing paradigms. The recently emerged reservoir …

Numerical weather prediction (NWP) has proven to be computationally challenging due to
its inherent multiscale nature. Currently, the highest resolution global NWP models use a …

Analyses and applications of big data require special technologies to efficiently process
large number of data. Mining association rules focus on obtaining relations between data …

SpMV (Sparse matrix–vector multiplication) is widely used in many fields. Improving the
performance of SpMV has been the pursuit of many researchers. Parallel SpMV using multi …

Von Neumann bottleneck, which refers to the limited throughput between the CPU and
memory, has already become a major factor hindering the technical advances of computing …