The U.S. Energy Department tested cloud providers on their ability to perform specific operations. "Early results from the Energy Department's Magellan cloud computing testbed suggest that commercially available clouds suffer in performance when operating Message Passing Interface (MPI) applications such as weather calculations, an official has said," according to this Federal Computer Week article.
MPI facilitates communications between processes and synchronizations between parallel processes. MPIs promote a discipline as well as a communication mechanism, making sure these programs remain in their specific domain and, thus, are easier to manage within a massively parallel environment. The Energy Department uses MPI-enabled applications for weather forecasting and for some chemistry research. Those doing the test stated that, while many commercial clouds give the "illusion of elasticity," there are logical and physical limits within cloud providers.
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This brings to light points I've been stressing for the last couple of years, including the fact that not all applications are right for the cloud. To that end, cloud providers are not optimized for specific types of applications, including MPI. However, this does not mean that clouds are slow and not scalable; they are just slow and not scalable when leveraged in a particular way.
Indeed, the Energy Department did find for computations that can be performed serially, such as genomics calculations, "there was little or no deterioration in performance." I suspect that with a bit of tuning on the provider's side, the MPI performance issues could be reduced as well. However, I doubt it could be eliminated completely, considering how public clouds are architected.