This is the second post in a series covering parallel processing in SAS Viya. The first post served as an introduction to parallel processing. It covered parallel processing uses in data science and the SAS Viya products that facilitate it. There are countless opportunities for using parallel processing within data
SAS' Leonid Batkhan presents an implementation of parallel processing by spawning multiple SAS sessions using SYSTASK statements with subsequent synchronization.
Most computers can execute operations in parallel due to their multicore infrastructure. Performing more than one operation simultaneously has the potential to speed up most tasks and has many practical uses within the field of data science. SAS Viya offers several products that facilitate parallel task execution. Many of these
According to the World Cancer Research Fund, Breast cancer is one of the most common cancers worldwide, with 12.3% of new cancer patients in 2018 suffering from breast cancer. Early detection can significantly improve treatment value, however, the interpretation of cancer images heavily depends on the experience of doctors and technicians. The
One of the hidden gems of SAS Studio is the ability to run process flows in parallel. This feature really shines when used in a grid environment. Let’s discuss this one step at a time. First, what is a process flow? When working in the Visual Programmer perspective, you have
I recently received a call from a colleague that is using parallel processing in a grid environment; he lamented that SAS Enterprise Guide did not show in the work library any of the tables that were successfully created in his project. The issue was very clear in my mind, but
Scalability is the key objective of high-performance software solutions. “Scaling out” is a concept which is accomplished by throwing more server machines at a solution so that multiple processes can run in dedicated environments concurrently. This blog post will briefly touch on several scalability concepts that affect SAS.
Do your SAS programs read extra-large volumes of data? Do they run multiple DATA steps and procedures one after the other for hours at a time? Two papers from MWSUG 2013 show how you can speed up those long-running SAS jobs. Although their approaches and environments differed, both authors made
