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Radar technology is used extensively by NASA for remote sensing of the Earth and other planetary bodies. In this case study, we learn about different computational concepts for processing radar data. In particular, we learn how to correct a slanted radar image by projecting it on the surface that was sensed by a radar instrument. The Web extra contains a Matlab data format file, as mentioned in the article. [ABSTRACT FROM AUTHOR]

J is an open source programming language with a rich collection of well-designed primitives and a consistent, compact, mathematics-like syntax. It has amazing array facilities, superb numeric and data processing capabilities, and graceful features allowing functions to be defined compactly. [ABSTRACT FROM PUBLISHER]

Techniques for library-centric application design have already proven to be very useful in the past. The current gain in computer performance is shifted towards the utilisation of multi-core processors which extends the importance of this type of application design in the field of scientific computing, which also poses new difficulties. A parallel generic scientific simulation environment has been developed to ease this transition from single-core to multi-core systems without additional development activity. [ABSTRACT FROM AUTHOR]

Addressing the scientific grand challenges identified by the US Department of Energy's (DOE's) Office of Science's programs alone demands a total leadership-class computing capability of 150 to 400 Pflops by the end of this decade. The successors to three of the DOE's most powerful leadership-class machines are set to arrive in 2017 and 2018-the products of the Collaboration Oak Ridge Argonne Livermore (CORAL) initiative, a national laboratory-industry design/build approach to engineering next-generation petascale computers for grand challenge science. These mission-critical machines will enable discoveries in key scientific fields such as energy, biotechnology, nanotechnology, materials science, and high-performance computing, and serve as a milestone on the path to deploying exascale computing capabilities. [ABSTRACT FROM AUTHOR]

Future large-scale parallel heterogeneous machines will likely need new programming approaches; X10 proposes one such alternative. [ABSTRACT FROM PUBLISHER]