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 …

Architectural and technological trends of systems used for scientific computing call for a
significant reduction of scientific data sets that are composed mainly of floating-point data …

Today's scientific simulations are producing vast volumes of data that cannot be stored and
transferred efficiently because of limited storage capacity, parallel I/O bandwidth, and …

We report on the successful completion of a 2 trillion particle cosmological simulation to z= 0
z=0 run on the Piz Daint supercomputer (CSCS, Switzerland), using 4000+ GPU nodes for a …

Multivariate time series are used in many science and engineering domains, including
health-care, astronomy, and high-performance computing. A recent trend is to use machine …

Error-bounded lossy compression is a state-of-the-art data reduction technique for HPC
applications because it not only significantly reduces storage overhead but also can retain …

Efficient error-controlled lossy compressors are becoming critical to the success of today's
large-scale scientific applications because of the ever-increasing volume of data produced …

ChaNGa is an N-body cosmology simulation application implemented using Charm++. In
this paper, we present the parallel design of ChaNGa and address many challenges arising …

Today's extreme-scale high-performance computing (HPC) applications are producing
volumes of data too large to save or transfer because of limited storage space and I/O …

Global checkpointing to external storage (eg, a parallel file system) is a common I/O pattern
of many HPC applications. However, given the limited I/O throughput of external storage …