Toward a Model for Shared Data Abstraction with Performance

This paper demonstrates the utility of typed shared data abstractions as an effective high-level means of structuring and coordinating parallel programs. Access to data shared by concurrent processes is expressed through operations of shared abstract data types (SADTs). SADTs abstract low-level concerns of communication and synchronization. The exposition addresses two major challenges: mismatches between representations and actual patterns of usage, and over-specified coherence. A prototype library of SADTs provides a set of implementations for each SADT, supporting stereotypical usage patterns and allowing exploitation of weakened coherence protocols. The efficacy of this approach is demonstrated on both a network of workstations and a dedicated massively parallel computer. A fine-grained irregular task-parallel computation obtained a speedup of 156 on a 256-processor Cray T3D, showing that the high levels of abstraction afforded by SADTs are compatible with efficient and scalable implementation. © 1998 Academic Press