Structured data access annotations for massively parallel computations

M. Aldinucci; S. Campa; M. Torquati; P. Kilpatrick

doi:10.1007/978-3-642-36949-0_42

Structured data access annotations for massively parallel computations

M. Aldinucci
, S. Campa
, M. Torquati
, P. Kilpatrick

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution

4 Citations (Scopus)

Abstract

We describe an approach aimed at addressing the issue of joint exploitation of control (stream) and data parallelism in a skeleton based parallel programming environment, based on annotations and refactoring. Annotations drive efficient implementation of a parallel computation. Refactoring is used to transform the associated skeleton tree into a more efficient, functionally equivalent skeleton tree. In most cases, cost models are used to drive the refactoring process. We show how sample use case applications/kernels may be optimized and discuss preliminary experiments with FastFlow assessing the theoretical results.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages	381-390
Number of pages	10
Volume	7640 LNCS
DOIs	https://doi.org/10.1007/978-3-642-36949-0_42
Publication status	Published - 01 Jan 2013

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10.1007/978-3-642-36949-0_42

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Structured data access annotations for massively parallel computations. / Aldinucci, M.; Campa, S.; Torquati, M. et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7640 LNCS 2013. p. 381-390.

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution

TY - CHAP

T1 - Structured data access annotations for massively parallel computations

AU - Aldinucci, M.

AU - Campa, S.

AU - Torquati, M.

AU - Kilpatrick, P.

PY - 2013/1/1

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N2 - We describe an approach aimed at addressing the issue of joint exploitation of control (stream) and data parallelism in a skeleton based parallel programming environment, based on annotations and refactoring. Annotations drive efficient implementation of a parallel computation. Refactoring is used to transform the associated skeleton tree into a more efficient, functionally equivalent skeleton tree. In most cases, cost models are used to drive the refactoring process. We show how sample use case applications/kernels may be optimized and discuss preliminary experiments with FastFlow assessing the theoretical results.

AB - We describe an approach aimed at addressing the issue of joint exploitation of control (stream) and data parallelism in a skeleton based parallel programming environment, based on annotations and refactoring. Annotations drive efficient implementation of a parallel computation. Refactoring is used to transform the associated skeleton tree into a more efficient, functionally equivalent skeleton tree. In most cases, cost models are used to drive the refactoring process. We show how sample use case applications/kernels may be optimized and discuss preliminary experiments with FastFlow assessing the theoretical results.

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AN - SCOPUS:84874434852

VL - 7640 LNCS

SP - 381

EP - 390

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -

Structured data access annotations for massively parallel computations

Abstract

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