Abstract
Supercomputers deliver a hundred- to millionfold performance compared to regular desktop PCs. This allows to tackle problems which could not be solved otherwise in a reasonable amount of time. At the same time, the massive amount of data generated and collected through sensors, experiments, etc., is constantly increasing, requiring new and analogously evolving approaches at hardware and software level for data processing and analysis. In this chapter, we shed light on recent hardware trends, programming paradigms, and software in the scope of high-performance computing and Big Data processing. We provide an overview of compute architectures, interwoven with programming examples, and discuss storage and data management concepts for both (super-)computing and Big Data processing. We further discuss performance metrics and benchmarking, as well as performance modeling and analysis for computing and data handling. Finally, we share some views on high-performance data analytics as well as concluding remarks on high-performance computing, Big Data, and convergence of these fields.
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