MPI shines mostly in the context of tightly-coupled applications operating on multiple nodes with a fast, reliable network. Most implementations are well-optim

MPI shines mostly in the context of tightly-coupled applications operating on multiple nodes with a fast, reliable network. Most implementations are well-optimized for operating on extremely high-bandwidth low-latency networks like Infiniband or Cray's Gemini. They can also use remote direct memory access (RDMA) to do cool stuff like let CUDA applications directly access GPU memory accross the network (GPUDirect). Scientific applications which involve a lot of interprocess communication -- for example, large CFD simulations -- can get a lot of benefits, especially since the popular MPI implementations are highly tuned for those types of apps. Also there's a ridiculous amount of legacy code, which leads to the usual lock-in effects. edit: clarification