Algebraic Approaches to Programming Concepts and Their      Semantics
{'Code': '05010400', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
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This project will pursue two related lines of research:  (a) the                semantics of parallel systems and programming constructs for parallel           computation; (b) the algebraic and analytic dynamics of large quasi-            neural networks for parallel computation.                                                                                                                       In (a), an investigation of programming constructs for vector                   computation will be carried out with multi-tasking as one of the main           approaches, as in Ada for example.  A theoretical foundation for                parallel algorithms will be sought within the framework of partially-           ordered sets of algebraic operations.  Some preliminary studies have            already suggested that Ada-like constructs are insufficient for                 efficient parallel numerical computations.  This finding will be placed         on a more rigorous basis by setting up a suitable algebraically-                oriented theory of multi-task algorithms, with particular attention to          asynchronism.                                                                                                                                                   In (b), studies will be continued on the dynamics of computational              systems.  However, the previous Turing network model will be replaced           by models based on networks of threshold-logic elements analogous to            McCulloch-Pitts neurons, which are called quasi-neurons.  Of particular         interest are the algebraic dynamics of such systems and the analytic            dynamics of special models of the quasi-neurons.  Related to part (a),          will be a study of the mathematical foundations of asynchronism in              quasi-neural networks.
{'FirstName': 'Edward', 'LastName': 'Blum', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Edward K Blum', 'EmailAddress': 'blum@pollux.usc.edu', 'NSF_ID': '000149479', 'StartDate': '09/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Southern California', 'CityName': 'LOS ANGELES', 'ZipCode': '90033', 'PhoneNumber': '2137407762', 'StreetAddress': '3720 S FLOWER ST FL 3', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '34', 'CONGRESS_DISTRICT_ORG': 'CA34', 'ORG_UEI_NUM': 'G88KLJR3KYT5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF SOUTHERN CALIFORNIA', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '287500', 'Text': 'SYSTEM SOFTWARE'}
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