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- University of Phoenix: Revolutionizing
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See how the University of Phoenix is using their SAS grid environment running on Sun systems to process and analyze many terabytes of data and optimize their marketing and advertising efforts. - Delivering the fastest time
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This white paper focuses on the evolution of grid computing with SAS and discusses the benefits it can bring to your organization, including increased performance, massive scalability and greater availability. The paper also includes several real-world examples of the power of SAS Grid Computing. -
SAS First to Automate Enterprise Grid Computing
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Industry's only vendor to grid-enable multiple applications, including data mining... - SAS Parallel Scoring Optimization
As data proliferates, organizations are taking advantage of data mining techniques to develop tactical and strategic insight into these vast data stores. Read how SAS parallel scoring can support an enterprise-class data mining operation.
SAS Grid Computing Downloads
This page contains various downloads to give you tools to make the most of your SAS grid environment.
Using SAS Enterprise Guide with SAS Grid Computing
The SASEGonGrid.zip file contains SAS code examples and sample SAS Enterprise Guide config files that facilitate the use of SAS Enterprise Guide on a grid. The zip file contains a readme.txt file that explains the purpose of each of the files contained in the zip file. Click here to download the zip file. You should also refer to the section "Using SAS Enterprise Guide with a SAS Grid" in the Grid Computing for SAS 9.2 documentation.
SAS Grid Computing Toolbox
The Grid Toolbox contains several tools to facilitate submission of SAS programs to a grid environment. Click here to download the grid toolbox. The following tools are included in this toolbox:-
Key Definition for Automatic Program Submission to the Grid (gridkeydef.doc)
If you prefer running an interactive DMS SAS Session, you can create a new key definition to allow you to submit your SAS program in its entirety to a grid environment with one easy keystroke. This new key definition will submit any code in your program editor to a SAS grid with absolutely no change to the SAS program. Your local workstation can be used for other processing while the grid takes care of your previous job. Upon completion, the results of your job are returned to your local workstation as if it had executed locally.
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Batch Submission of Programs from Windows to the Grid (runsas.cmd)
If you prefer running SAS in a command line or batch mode from a Windows workstation, this Windows cmd file will enable you to submit your SAS program in its entirety to a grid environment by simply invoking this cmd file. This cmd file will wrap your SAS program with the necessary syntax to submit your program to a SAS grid with absolutely no change to your SAS program. Your local workstation can be used for other processing while the grid takes care of your previous job. Upon completion, the results of your job are returned to your local workstation as if it had executed locally.
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Batch Submission of Programs from Unix to the Grid (runsas.sh)
If you prefer running SAS in a command line or batch mode from a Unix workstation, this Unix shell script will enable you to submit your SAS program in its entirety to a grid environment by simply invoking this shell script. This script will wrap your SAS program with the necessary syntax to submit your program to a SAS grid with absolutely no change to your SAS program. Your local workstation can be used for other processing while the grid takes care of your previous job. Upon completion, the results of your job are returned to your local workstation as if it had executed locally.
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The %Distribute Macro (GridDistribute.sas)
This SAS macro facilitates parallel distribution of SAS programs in a grid. If you have a SAS application that performs the same fundamental processing task multiple times against different subsets of data, this macro provides a template to facilitate execution of this program across a grid. GridDistribute.sas lets you run subtasks of an application in parallel on a grid and aggregate partial results back together into a final result set. Applications that lend themselves to this type of processing can see huge performance gains in the 90% range.
