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Title: OpenMP-style parallelism in data-centered multicore computing with R

Abstract

R is a domain specific language widely used for data analysis by the statistics community as well as by researchers in finance, biology, social sciences, and many other disciplines. As R programs are linked to input data, the exponential growth of available data makes high-performance computing with R imperative. To ease the process of writing parallel programs in R, code transformation from a sequential program to a parallel version would bring much convenience to R users. In this paper, we present our work in semiautomatic parallelization of R codes with user-added OpenMPstyle pragmas. While such pragmas are used at the frontend, we take advantage of multiple parallel backends with different R packages. We provide flexibility for importing parallelism with plug-in components, impose built-in MapReduce for data processing, and also maintain code reusability. We illustrate the advantage of the on-the-fly mechanisms which can lead to significant applications in data-centered parallel computing.

Authors:
 [1];  [2];  [2];  [3]
  1. Louisiana State University
  2. ORNL
  3. Technical University, Munich, Germany
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE; Work for Others (WFO)
OSTI Identifier:
1051480
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming, New Orleans, LA, USA, 20120225, 20120225
Country of Publication:
United States
Language:
English

Citation Formats

Jiang, Lei, Patel, Pragneshkumar B, Ostrouchov, George, and Jamitzky, Ferdinand. OpenMP-style parallelism in data-centered multicore computing with R. United States: N. p., 2012. Web.
Jiang, Lei, Patel, Pragneshkumar B, Ostrouchov, George, & Jamitzky, Ferdinand. OpenMP-style parallelism in data-centered multicore computing with R. United States.
Jiang, Lei, Patel, Pragneshkumar B, Ostrouchov, George, and Jamitzky, Ferdinand. Sun . "OpenMP-style parallelism in data-centered multicore computing with R". United States. doi:.
@article{osti_1051480,
title = {OpenMP-style parallelism in data-centered multicore computing with R},
author = {Jiang, Lei and Patel, Pragneshkumar B and Ostrouchov, George and Jamitzky, Ferdinand},
abstractNote = {R is a domain specific language widely used for data analysis by the statistics community as well as by researchers in finance, biology, social sciences, and many other disciplines. As R programs are linked to input data, the exponential growth of available data makes high-performance computing with R imperative. To ease the process of writing parallel programs in R, code transformation from a sequential program to a parallel version would bring much convenience to R users. In this paper, we present our work in semiautomatic parallelization of R codes with user-added OpenMPstyle pragmas. While such pragmas are used at the frontend, we take advantage of multiple parallel backends with different R packages. We provide flexibility for importing parallelism with plug-in components, impose built-in MapReduce for data processing, and also maintain code reusability. We illustrate the advantage of the on-the-fly mechanisms which can lead to significant applications in data-centered parallel computing.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 2012},
month = {Sun Jan 01 00:00:00 EST 2012}
}

Conference:
Other availability
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