Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.618387
Title: Domain-specific languages for massively parallel processors
Author: Cartey, Luke
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2013
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Abstract:
Massively Parallel Processors provide significantly higher peak performance figures than other forms of general purpose processors. However, this comes at a cost to the developer, who needs to deal with an increasingly complicated piece of hardware, for which applications need to be tweaked and optimised to achieve high performance. Domain-specific languages have been proposed as a potential solution to this complexity problem: generating GPU applications from high-level, declarative specifications. This thesis explores two related ideas: firstly, is it practical to synthesise DSLs from high-level languages, and secondly, how can we simplify the creation of such DSLs? This thesis proposes a novel approach whereby rather than considering single domains, we consider collections of collaborative domains in order to share common features and thus reduce the cost of development. We achieve this using a DSLs-within-a-DSL approach: a custom designed host language, into which extensions may be embedded. In order to ground our approach in a real case-study, we propose, design and develop a DSLs-within-a-DSL framework for bioinformatics. We use a restricted recursive functional language as the host language, and embed new DSLs into this language. Importantly, we describe how we can use a combination of novel and adopted automatic parallelisation techniques to synthesise a massively-parallel program for a GPU. This automatic parallelisation, achieved through the discovery of a schedule, and program synthesis techniques using the polyhedral model, interacts productively with our embedded extensions. To further simplify development, we provide a series of customisable heuristics for defining GPU parameters such as the block size (number of threads), grid size and location in the memory hierarchy of data-structures. This encapsulates GPU expertise within the compiler itself. We finally demonstrate that the total combination of these techniques results in applications with competitive performance, at much lower development cost and greater flexibility than comparable hand-coded applications.
Supervisor: de Moor, Oege; Hein, Jotun Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.618387  DOI: Not available
Keywords: Program development and tools ; Bioinformatics (technology) ; graphics cards ; domain-specific languages ; bioinformatics ; program analysis
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