Graduate Thesis Or Dissertation
 

Task-parallel extension of a data-parallel language

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/pr76f682q

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  • Two prevalent models of parallel programming are data parallelism and task parallelism. Data parallelism is the simultaneous application of a single operation to a data set. This model fits best with regular computations. Task parallelism is the simultaneous application of possibly different operations to possibly different data sets. This fits best with irregular computations. Efficient solution of some problems require both regular and irregular computations. Implementing efficient and portable parallel solutions to these problems requires a high-level language that can accommodate both task and data parallelism. We have extended the data-parallel language Dataparallel C to include task parallelism so that programmers may now use data and task parallelism within the same program. The extension permits the nesting of data-parallel constructs inside a task-parallel framework. We present a banded linear system to analyze the benefits of our language extensions.
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Déclaration de droits
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  • File scanned at 300 ppi (Monochrome, 256 Grayscale) using Capture Perfect 3.0 on a Canon DR-9050C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
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