<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>3548</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>39</pageFirst>
    <pageLast>46</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>ACM</publisherName>
    <publisherPlace>New York, NY, USA</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A High-Performance Image Processing DSL for Heterogeneous Architectures</title>
    <abstract language="eng">Over the last decade a number of high performance, domain-specific languages (DSLs) have started to grow and help tackle the problem of ever diversifying hard- and software employed in fields such as HPC (high performance computing), medical imaging, computer vision etc. Most of those approaches rely on frameworks such as LLVM for efficient code generation and, to reach a broader audience, take input in C-like form. In this paper we present a DSL for image processing that is on-par with competing methods, yet its design principles are in strong contrast to previous approaches. Our tool chain is much simpler, easing the burden on implementors and maintainers, while our output, C-family code, is both adaptable and shows high performance. We believe that our methodology provides a faster evaluation of language features and abstractions in the domains above.</abstract>
    <parentTitle language="eng">Proceedings of the 9th European Lisp Symposium (ELS 2016), Krakow, Poland</parentTitle>
    <identifier type="isbn">978-2-9557474-0-7</identifier>
    <identifier type="url">https://selgrad.org/publications/2016_els_SLDRS.pdf</identifier>
    <enrichment key="opus.import.date">2022-04-21T06:30:05+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Kai Selgrad</author>
    <author>Alexander Lier</author>
    <author>Jan Dörntlein</author>
    <author>Oliver Reiche</author>
    <author>Marc Stamminger</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Common Lisp</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Domain Specific Langauges</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Generative Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Meta Programming</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
</export-example>
