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Article . 2015
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Go Meta! A Case for Generative Programming and DSLs in Performance Critical Systems

descriptionPublicationkeyboard_double_arrow_right Conference object , Article 01 Jan 2015Embargo end date: 01 Jan 2015 English Publisher:ETH Zurich
Authors: Rompf, Tiark; Brown, Kevin J.; Lee, HyoukJoong; Sujeeth, Arvind K.; Jonnalagedda, Manohar; Amin, Nada; Ofenbeck, Georg; +6 Authors

doi: 10.3929/ethz-b-000111987

handle: 20.500.11850/111987

Go Meta! A Case for Generative Programming and DSLs in Performance Critical Systems

Abstract

Most performance critical software is developed using very low-level techniques. We argue that this needs to change, and that generative programming is an effective avenue to enable the use of high-level languages and programming techniques in many such circumstances.

Leibniz International Proceedings in Informatics (LIPIcs), 32

1st Summit on Advances in Programming Languages (SNAPL 2015)

ISBN:978-3-939897-80-4

ISSN:1868-8969

Related Organizations
Keywords

Staging, Performance, Performance; Generative Programming; Staging; DSLs, 650, DSLs, 004, Generative Programming, ddc: ddc:004

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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