Abstract state machines for data-parallel computing

Qing Wang

doi:10.1007/978-3-642-28279-9_11

Abstract state machines for data-parallel computing

Qing Wang^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

The current programming paradigm for data-parallel computations is shifting with the rapidly increasing data growth on the web. It gives programmers more challenges than ever before. In this paper we propose Parallel Abstract State Machines (P-ASMs) that can empower programmers, no matter how experienced, by providing a well-founded systems engineering method to model data-parallel computations at arbitrary levels of abstraction. Particularly, we focus on discussing how P-ASMs can capture two classes of data-parallel computations that are most important in practice - ones that are always-consistent and ones that require transactional data consistency.

Original language	English
Title of host publication	Conceptual Modelling and Its Theoretical Foundations
Subtitle of host publication	Essays Dedicated to Bernhard Thalheim on the Occasion of His 60th Birthday
Publisher	Springer Verlag
Pages	136-150
Number of pages	15
ISBN (Print)	9783642282782
DOIs	https://doi.org/10.1007/978-3-642-28279-9_11
Publication status	Published - 2012
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7260 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

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10.1007/978-3-642-28279-9_11

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Wang, Q. (2012). Abstract state machines for data-parallel computing. In Conceptual Modelling and Its Theoretical Foundations: Essays Dedicated to Bernhard Thalheim on the Occasion of His 60th Birthday (pp. 136-150). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7260 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-642-28279-9_11

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abstract = "The current programming paradigm for data-parallel computations is shifting with the rapidly increasing data growth on the web. It gives programmers more challenges than ever before. In this paper we propose Parallel Abstract State Machines (P-ASMs) that can empower programmers, no matter how experienced, by providing a well-founded systems engineering method to model data-parallel computations at arbitrary levels of abstraction. Particularly, we focus on discussing how P-ASMs can capture two classes of data-parallel computations that are most important in practice - ones that are always-consistent and ones that require transactional data consistency.",

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language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "136--150",

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Wang, Q 2012, Abstract state machines for data-parallel computing. in Conceptual Modelling and Its Theoretical Foundations: Essays Dedicated to Bernhard Thalheim on the Occasion of His 60th Birthday. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7260 LNCS, Springer Verlag, pp. 136-150. https://doi.org/10.1007/978-3-642-28279-9_11

Abstract state machines for data-parallel computing. / Wang, Qing.
Conceptual Modelling and Its Theoretical Foundations: Essays Dedicated to Bernhard Thalheim on the Occasion of His 60th Birthday. Springer Verlag, 2012. p. 136-150 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7260 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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Wang Q. Abstract state machines for data-parallel computing. In Conceptual Modelling and Its Theoretical Foundations: Essays Dedicated to Bernhard Thalheim on the Occasion of His 60th Birthday. Springer Verlag. 2012. p. 136-150. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-28279-9_11

Abstract state machines for data-parallel computing

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