pbdR Tech -- Programming with Big Data in R (Technical Site)

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Section: pbdR Tech

What is this?

This is a website about ``Programming with Big Data in R'' and provide several R packages. We develop pbdR packages and focus on analyzing big data by utilizing Statistics methodology. All packages mainly support the SPMD programming model with special focus on large scale computing clusters. Packages are available in the Download and instruction for Installation is also available. Some basic examples can be found in the Cookbook section of HPSC website.

Official Website

The Programming with Big Data in R (pbdR) has an official website at http://r-pbd.org/ . The information remaining here is for internal development, technical discussion, and windows binary download. Other useful resources are all avaialbe via

Authors

Wei-Chen Chen, George Ostrouchov, Pragneshkumar Patel, and Drew Schmidt.

Acknowledgment

George Ostrouchov and Wei-Chen Chen were supported in part by the project ``Visual Data Exploration and Analysis of Ultra-large Climate Data'' funded by U.S. DOE Office of Science under Contract No. DE-AC05-00OR22725. George Ostrouchov, Drew Schmidt, and Pragneshkumar Patel were supported in part by the project ``NICS Remote Data Analysis and Visualization Center'' funded by the Office of Cyberinfrastructure of the U.S. National Science Foundation under Award No. ARRA-NSF-OCI-0906324 for NICS-RDAV center.

This work used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This work also used resources of National Institute for Computational Sciences at the University of Tennessee, Knoxville, which is supported by the Office of Cyberinfrastructure of the U.S. National Science Foundation under Award No. ARRA-NSF-OCI-0906324 for NICS-RDAV center. This work used resources of the Newton HPC Program at the University of Tennessee, Knoxville.

We thank our colleagues from the Scientific Data Group, Computer Science and Mathematics Division, Oak Ridge National Laboratory, Hasan Abbasi, Jong Youl Choi, Scott Klasky, and Nobert Podhorszki for discussing windows MPI systems, compiler issues, dynamic libraries, and generally improving our knowledge of MPI performance issues. We also thank our colleague, Ed D'Azevedo from the Computational Mathematics Group, Computer Science and Mathematics Division, Oak Ridge National Laboratory, for his discussions and illuminating advice using ScaLAPACK and distributed matrix computation.

We specially thank Brian D. Ripley, Kurt Hornik, Uwe Ligges, and Simon Urbanek from the R Core Team for discussing package release issues and helping us solve portability problems on different platforms.

This website is built on a machine located in the Department of Statistics at Iowa State University in Ames Iowa, USA.

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Created: Sep 23 2012
Last Revised: Apr 05 2014, 04:01 (CDT Ames, IA, USA)
Maintained: Wei-Chen Chen
E-Mail: wccsnow @ gmail.com
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