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The first is the ongoing emergence of multicore and hybrid microprocessor designs, ushering in a new era of computing in which system designers must accept energy usage as a first-order constraint, and application designers must be able to exploit parallelism and data locality to an unprecedented degree. The research areas of cluster, cloud, and data analytics computing, which today provide fundamental infrastructure for all areas of advanced computational science, are being radically transformed by the convergence of at least two unprecedented trends. [Extracted from the article]

Synthetic aperture radar (SAR) interferometry has rapidly evolved in the last decade and can be considered today as a mature technology, which incorporates computationally intensive and data-intensive tasks. In this paper, a perspective on the state-of-the-art of high performance computing (HPC) methodologies applied to spaceborne SAR interferometry (InSAR) is presented, and the different parallel algorithms for interferometric processing of SAR data are critically discussed at different levels. Emphasis is placed on the key processing steps, which typically occur in the interferometric techniques, categorized according to their computational relevance. Existing implementations of the different InSAR stages using diverse parallel strategies and architectures are examined and their performance discussed. Furthermore, some InSAR computational schemes selected in the literature are analyzed at the level of the entire processing chain, thus emphasizing their potentialities and limitations. Therefore, the survey focuses on the inherent computational approaches enabling large-scale interferometric SAR processing, thus offering insight into some open issues, and outlining future trends in the field. [ABSTRACT FROM AUTHOR]

The Baker Hughes high-performance computing environment is deploying a three-tier approach to providing technical computing resources as an alternative to typical high-performance computing. Baker Hughes uses a complete spectrum of computer resources that break from the standards of high-density, dedicated resources. This environment is intended to provide a more flexible and efficient approach that is responsive to business needs. The design has been proven in production systems in the United States and the Russian Federation since the second quarter of 22001100 with multiple proprietary and in-house scientific applications. This paper will discuss a computing infrastructure that Baker Hughes has built to better adapt to meet changing requirements in high-performance computing. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including the workshop on clusters, cloud and data for scientific computing (CCDSC), scientific parallel computing, and high performance computing.