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High Performance Computing for Mission-Enabling Space Applications
Author(s) -
Charles D. Norton
Publication year - 2007
Publication title -
scientific programming
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.269
H-Index - 36
eISSN - 1875-919X
pISSN - 1058-9244
DOI - 10.1155/2007/105856
Subject(s) - spacecraft , outreach , computer science , monte carlo method , space exploration , systems engineering , descent (aeronautics) , aerospace engineering , supercomputer , simulation , operating system , engineering , statistics , mathematics , political science , law
These demands are driven by factors tied directly to JPL’s future mission set. For example, in some regimes physical testing cannot be performed and/or the cost of performing extensive validation in a physical testbed is prohibitively expensive. The design exploration space for project risk reduction, first principles simulation and data mining to discover new physical phenomena of interest, the need to produce high quality animations in a timely fashion, and design-trade studies for engineering analysis are also driving JPL’s needs for High Capability Computing (HCC) to meet our mission challenges. High Capability Computing involves the use of parallel computer systems (those with hundreds to thousands of processors) to solve a large problem more rapidly than a desktop computer system and/or to solve many variations of a specific problem simultaneously. This is an enabling capability for addressing the most advanced problems in science and engineering. High Capability Computing also includes development of computational technologies that both improve the fidelity of existing applications and spawn the generation of new ones. JPL maintains HCC systems within labs at the group, flight project, and institutional level. Furthermore, with various partners, JPL develops world-class science and engineering analysis software. Many, particularly Earth observing missions, have used HCC in some form since JPL acquired initial systems in the early 1990s. Although one of the main drivers at that time was computational electromagnetics modeling even a few planetary missions, such as Magellan (1989), later benefited from HCC for comnbining radar surface topography data with digital elevation maps to produce visualizations of virtual flyovers of the Venetian surface. Such efforts span from re-processing of past data sets to very recent work such as the calculation of gravity fields, and other measurements, from the Gravity Recovery and Climate Experiment (GRACE) mission. As the technology and our infrastructure advanced so have our capabilities. JPL and Caltech helped pioneer and establish the area of supercomputing in the mid-80s with development

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