That is exactly what weather simulations do. Same most other kinds of hydrodynamic simulations (simulation of gas or fluid flows).
The thing is: you need the state at t-1 of all your neighbors. Then you can do a small timestep to get from t-1 to time t. And then you need the NEW state of your neighbors. That requires a fast interconnect. Which HPC machines have, unlike most clouds or commodity clusters.
In other words, yes it is parallelizable, but not trivially so, because the different grid points are coupled.
I’ve seen that azure has some nodes with infiniband connection (same that is often used in super computers).
I did my PhD in physics simulations (molecular dynamics), and have the same problem there. I tried running these simulations in Google Cloud without any good performance results due to high latency (compared to HPC). I’m no GC expert though, so should be possible to improve what I did.
The thing is: you need the state at t-1 of all your neighbors. Then you can do a small timestep to get from t-1 to time t. And then you need the NEW state of your neighbors. That requires a fast interconnect. Which HPC machines have, unlike most clouds or commodity clusters.
In other words, yes it is parallelizable, but not trivially so, because the different grid points are coupled.