How to distribute the case in parallel computing?
 

I have a large unsteady LES case, my grid number would be around 10 million, that is 10,000,000, so I don’t know how to make the best use of the parallel computing. How to distribute the grids to each cpu so to make the simulation most efficient? How many grids a single cpu and a single node bear with highest efficiency?

I know the question is kind of general, but could you give me also both general guidelines for it, and also your detailed experience, for example, one of your large cases, how you distribute it.

Thank you so much.

Fluent will distribute the model for you, as long as you start it in parallel mode. From the Fluent "startup" panel, you have the option to select a parallel solution as well as the number of processors.

There are ways within Fluent to decompose the model across processors manually, but typically the automatic mesh partitioner does the job very well.

But I mean how many grid points for each cpu, any guidelines?

The answer depends on the memory associated with each processor, and the nature of the physics you are solving. The more complicated the physics, the more memory overhead. You could probably solve your LES model with 10 million cells on a machine with around 24 GB of RAM.