High-Performance Statistical Modeling
Robert Alan Cohen, Robert N. Rodriguez · 2013
The explosive growth of data, coupled with the emergence of powerful distributed computing platforms, is driving the need for high-performance statistical modeling software. SAS has developed a group of high-performance analytics procedures that perform statistical modeling and model selection by exploiting all the cores available—whether in a single machine or in a distributed computing environment. This paper describes the various execution modes and data access methods for high-performance analytics procedures. It also discusses the design principles for high-performance statistical modeling procedures and offers guidance about how and when these procedures provide performance benefits.