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 …

Existing systems for video-based pose estimation and tracking struggle to perform well on
realistic videos with multiple people and often fail to output body-pose trajectories consistent …

Today's scientific simulations require a significant reduction of the data size because of
extremely large volumes of data they produce and the limitation of storage bandwidth and …

Topological data analysis offers a rich source of valuable information to study vision
problems. Yet, so far we lack a theoretically sound connection to popular kernel-based …

As Linux clusters have matured as platforms for low-cost, high-performance parallel
computing, software packages to provide many key services have emerged, especially in …

Dataset storage, exchange, and access play a critical role in scientific applications. For such
purposes netCDF serves as a portable, efficient file format and programming interface …

Applications running on leadership platforms are more and more bottlenecked by storage
input/output (I/O). In an effort to combat the increasing disparity between I/O throughput and …

Develo** and tuning computational science applications to run on extreme scale systems
are increasingly complicated processes. Challenges such as managing memory access and …

Mega, 471 memory, 43, 54 cache, 33, 35, 44 DRAM, 44 SRAM, 44 mesh regular, 174
message box, 296 message latency, 207 message passing, 161, 237, 296 Message …