{'fraction_non_alphanumeric': 0.01675977653631285, 'fraction_numerical': 0.0074487895716946, 'mean_word_length': 5.6770186335403725, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Towards a Model for Shared Data Abstraction with Performance 2 by

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 synchronisation. 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 workstationsand a dedicated massively parallel computer. A fine-grained irregular 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.