Computer architectures continue to evolve and expose additional hardware parallelism to software applications. Although programming systems can leverage advances in hardware parallelism for the processing of numerical data, finding ways to exploit additional hardware parallelism for text data is particularly challenging. To address this challenge we define s2k, a global-view parallel programming language for streaming text extraction and transformations that integrates stream programming abstractions and parallel bitstream programming methods. The s2k language design involves several aspects. First, the design of domain-specific abstractions that integrate stream programming concepts and parallel bitstream programming methods. Second, the definition of a deterministic parallel programming model with serial semantics. Third, the design of a translation scheme to transform s2k stream programs into a portable intermediate language suitable for translation to backend representations. Fourth, the definition of s2k runtime libraries for parallel text processing.
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Thesis advisor: Cameron, Robert D.
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