in High Performance Computing, there is (1) 3-dimensional simulations (weather, fluid dynamics, structural mechanics, all kinds of physics simulations, like magnetic storms in space or nuclear reactors etc.) and then there is (2) everything else, like data mining, machine learning, genomics etc.

Some of the sparse matrix computations in structural mechanics and in some machine learning algorithms have some overlap. But mostly, group 2 has little reason to be interested in what group 1 is doing.

Now, group 2 obviously has more modern tools than the 3d-simulation community, because machine learning came to common use much later that numerical fluid mechanics.

But do 3d-simulation people also have much reason to be interested in what the machine learning people are doing?

The "machine learning / big data" people are probably not doing anything that makes a weather prediction model to run faster? Or are they?