[gruseom]

Interesting; thanks.

What you're describing sounds to me like the complexity of ferrying data around and scheduling computations is being offloaded to the app programmer. Presumably the intent behind things like OpenMP on clusters is to take care of all that behind the scenes and let the user pretend that it's all shared and program accordingly. Is that correct? If so, how far would you say such distributed infrastructure has gotten to date? Is it usable for real work, or do people end up having to learn so many limitations and workarounds that they're no better off than programming against the lower-level model in the first place?

Another question: even when there is shared memory you still have to coordinate the various processes that are operating concurrently on it so they don't clobber each other, and that, as everyone knows, is complicated too. So there is a tradeoff here. It sounds like your point is that given a choice, the HPC community would rather program against shared memory using traditional concurrency mechanisms (threads, locks, etc.) than deal with the complexities of the alternatives. Am I reading you correctly? If so, that's a pretty major point which suggests that the general-purpose programming community may be gearing up for a wild goose chase.