ABSTRACT
High Performance Computing (HPC) is used to solve a number of complex questions in computational and data-intensive sciences. These questions include the simulation and modeling of physical phenomena, such as climate change, energy production, drug design, global security, and materials design; the analysis of large data sets, such as those in genome sequencing, astronomical observation, and cybersecurity; and, the intricate design of engineered products, such as airplanes and automobiles. By any measure, the past 17 years from 1997 have witnessed dramatic increases in both the use and scale of HPC. Thinking back, it was 1997, only 17 years ago, when the ASCI Red system at Sandia National Laboratories in Albuquerque, New Mexico, broke the 1 Terascale barrier on TOP500 Linpack using 7,264 Pentium P6 processors over a proprietary interconnection network. Scientific data management and visualization software provides users with domain specific tools for generating, managing, and exploring data for their science.
