Now, to prevent misunderstanding, I should mention that these are some massive domains that could benefit greatly from a high level, parallel model. I cannot co

Now, to prevent misunderstanding, I should mention that these are some massive domains that could benefit greatly from a high level, parallel model. I cannot count the number of times I asked "How do I parallelize this trivially parallelizable program" and not been able to find any answer more specific that "trivially". This is a large part of my motivation for working on data-parallel languages -- the parallel programming tools we have are generally good at making easy problems hard. I agree that the domain of highly regular data-parallel computation is large (given the attention going to GPGPU), enough so to warrant its own high-level language. APL already has a convenient and flexible (user-level) programming model for this but carries along enough ad hoc limitations and weird corner cases to make a good parallelizing compiler infeasible. Maybe someone will eventually come up with a general-purpose parallel language that offers a smooth transition from the easy parallelism to the hard (concurrent) parallelism, but so far everything I've seen that accommodates concurrency complicates the non-concurrent cases in doing so.