General Performance Considerations
This section discusses some issues that you may find generally useful in parallelizing R applications. I’ll present some material on the main sources of overhead and then discuss a couple of algorithmic issues.
Sources of Overhead
Having at least a rough idea of the physical causes of overhead is essential to successful parallel programming. Let’s take a look at these in the contexts of the two main platforms, shared-memory and networked computers.
Shared-Memory Machines
As noted earlier, the memory sharing in multicore machines makes for easier programming. However, the sharing also produces overhead, since the two cores will bump into each other if they both try to access memory at the same time. This means that ...
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