Speed is often most crucial when performing computationally intense estimation procedures. A few of Stata’s estimation procedures, including linear regression, are nearly perfectly parallelized, meaning they run twice as fast on two cores, four times as fast on four cores, eight times as fast on eight cores, and so on. Some estimation commands can be parallelized more than others. Taken at the median, estimation commands run 1.8 times faster on 2 cores, 3.1 times faster on 4 cores, and 4.2 times faster on 8 cores.

Speed can also be important when managing large datasets. Adding new variables is nearly 100 percent parallelized, and sorting is 75 percent parallelized.

Some procedures are not parallelized and some are inherently sequential, meaning they run the same speed in Stata/MP.

For a complete assessment of Stata/MP’s performance, including command-by-command statistics, see theĀ Stata/MP Performance Report