Enhanced Data and Task Abstractions for Extreme-scale Runtime Systems

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dc.contributor.advisorSarkar, Vivek
dc.creatorVrvilo, Nick
dc.date.accessioned2019-05-16T20:18:17Z
dc.date.available2019-05-16T20:18:17Z
dc.date.created2017-08
dc.date.issued2017-08-10
dc.date.submittedAugust 2017
dc.date.updated2019-05-16T20:18:17Z
dc.description.abstractRecently, we’ve seen a variety of emerging programming models targeting the next generation of HPC hardware, known as extreme-scale computing systems. Extreme-scale runtime systems need to address not only the problems presented by supporting new hardware, but also issues of scalability—whether in small-scale embedded environments or large-scale supercomputing clusters. While a runtime may present all of the necessary functionality to write software for an extreme-scale system, the runtime APIs are rarely a productive interface for application programmers. In this thesis, we present a set of abstractions, which are designed to be implemented on top of an extreme-scale runtime, that will increase programmability and productivity for software developers. These ab-stractions include support for blocking calls in a fine-grained task-based runtime, a data structure representation for relocatable data chunks, and a hierarchical model for design and analysis of macro-dataflow applications. We discuss and demonstrate the tradeoffs among implementation choices for these abstractions, since the specific hardware and soft- ware details of an application deployment may dictate the ideal method of implementing a given abstraction.
dc.format.mimetypeapplication/pdf
dc.identifier.citationVrvilo, Nick. "Enhanced Data and Task Abstractions for Extreme-scale Runtime Systems." (2017) Diss., Rice University. <a href="https://hdl.handle.net/1911/105497">https://hdl.handle.net/1911/105497</a>.
dc.identifier.urihttps://hdl.handle.net/1911/105497
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectexascale computing
dc.subjectextreme-scale computing
dc.subjectopen community runtime
dc.subjectconcurrent collections
dc.titleEnhanced Data and Task Abstractions for Extreme-scale Runtime Systems
dc.typeThesis
dc.type.materialText
thesis.degree.departmentComputer Science
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
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