I am using Knime and R to analyze a large dataset. I am using Knime filter nodes to select a subset of my data which I then pass to R. When I wanted to filter my data in a different manner and perform the same test in R, rather than create a separate Knime workflow I duplicated my connected nodes into the same workflow such that I have two parallel workflows each with it's own end node If I execute both of these workflows at the same time they both begin processing. If I use top to view the cpu and memory utilization of the R processes on my linux machine, I see a single R process. I had expected that when I executed both workflows at the same time I would see two R processes, one for each group of connected nodes.
Is there a way to configure my workflow such each group of nodes will execute a separate R process and thereby utilize the resources of my computer more efficiently?