White Papers
A Generic Method of Parallel Processing in Base SAS 8 and 9
Overview Parallel processing or multi-threading a SAS job is a mode of execution in which two or more portions of a job run in parallel streams to accelerate processing and reduce the real time to completion. Performance gain is achieved by simultaneously using multiple processors which can benefit from added CPU power as well as multiple I/O channels. For this reason multi-threading is more meaningful when the hardware has multiple CPUs such as a Unix machine or a multi-processor Windows server. The case scenario discussed in this paper is specifically for a Unix machine but the logic can be applied to Windows with some modifications for operating system differences.
- Publisher
- SAS Institute
- File Format
- Date Published
- Jun 2, 2007
- Format
- White Papers
- Topics
- Parallel Processing, UNIX, Software Engineering
SAS Institute White Papers
A Clever Demonstration of the SAS SUBSTR Function
The SAS SUBSTR function differs from the substring function in other programming languages as it can be used on either s
Publisher: SAS Institute
Understanding Your Customer: Segmentation Techniques for Gaining Customer Insight and Predicting Risk in the Telecom Industry
The explosion of customer data in the last twenty years has increased the need for data mining aimed at Customer Relatio
Publisher: SAS Institute | Tags: crm, customer service, data, data mining
An Animated Guide: Proc Transpose
If one can think about a SAS data set as being made up of columns and rows, one can say Proc Transpose "Flips" the colum
Publisher: SAS Institute | Tags: data
Cool New Features in SAS Enterprise Miner 5.3
SAS released Enterprise Miner 5.3 in late 2007 with a veritable plethora of cool new features for data miners everywhere
Publisher: SAS Institute | Tags: data, software
An Introduction to SAS Character Functions
SAS software is especially rich in its assortment of functions that deal with character data. This class of functions is
Publisher: SAS Institute | Tags: data, software
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