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You can’t put down shingles until the decking is there, and you can’t nail down the decking unless you have the rafters in place. So, instead of hiring three teams to do these three tasks in parallel, you can hire one roofing crew to do all three in the order required (there is parallelism within each of the roofing steps, plus the act of putting on the roof is independent of installing the electrical wiring, the plumbing, and putting up drywall). To satisfy an execution order constraint, you can schedule tasks that have an order dependency onto the same thread and ensure that the thread executes the tasks in the proper sequence.

Mixing exchange and update computations can complicate the logic of your application, especially to ensure correct data is retrieved. However, the serial application likely had this requirement, too, and the solution to the need for accessing correct data concurrently should simply follow the serial algorithm as much as possible. For example, if you are modeling the distribution of heat from a source through a metal plate, you can simulate the plate by a two-dimensional array of current temperatures at discrete spatial locations.

Several different synchronization mechanisms are available (usually dependent on the threading method you are using) to provide mutual exclusion. Both reading and writing of data must be protected. Multiple threads reading the same data won’t cause any problems. When you have multiple threads writing to the same location, the order of the updates to the memory location will determine the value that is ultimately stored there and the value that will be read out of the location by another thread (recall the airline reservation system that put two passengers in the same seat).

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