Abstract
The evolution in parallel programming languages is toward implicit parallelism, and toward virtual parallelism: Explicitly coding for parallelism is to be avoided; coding for the physical machine size is a low-level programming practice to be overcome as soon as possible. Our examples indicate this may not be possible in general — although it might well be a realistic alternative for many numerical codes with simple structure. Much emphasis is now put on data-parallel languages, where parallelism is implied from the use of aggregate operations on data aggregate (mostly array operations on data arrays); parallelism is derived from parallel execution of these aggregate operations or derived from a data partition. Our examples imply that control parallelism, where parallelism is derived from explicit user allocation of operations to (virtual or physical) processors is necessary to express certain algorithms.
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