查看文章

Parallel computing has typically emphasized systems that can be explicitly decomposed into independent subunits with minimal interactions. For example, most parallel processing systems achieve speedups by identifying code and data segments that can be executed simultaneously. Under this approach, interactions among the various segments are managed directly, through synchronization, and communication among components is viewed as an inherent cost of computation. As a result, most extant parallel systems require substantial amounts of overhead to manage and coordinate the activities of the various processors, and they obtain speedups that are considerably less than a linear function of the number of processors.

An alternative approach exploits the interactions among simultaneous computations to improve efficiency, increase flexibility, or provide a more natural representation. Researchers in …