Independent tables derived from the same source tables are executed in parallel (see below):
In addition, you can split your dataset into two or three partitions, and then for each partition call a module pass a partition to that module using the “Input” action, and then inside the module divide it again into two or three derived tables with an “Iterate web request” in each. Using this technique you can achieve degrees of parallelism 4, 9, 16, and more.
Remember, however, that the number of actions executed in parallel depends on the number of CPU cores on your machine that runs EasyMorph. EasyMorph never spans more computational threads than CPU cores on the machine that runs the workflow.
Therefore for higher parallelism, run workflows on a machine with more CPU cores. See also this reply: Question: What controls the limits of how many actions can be executed simultaneously? - #4 by Denys_Isaev