Parallel Computing for Large-Scale Optimization
{'Code': '05010500', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
{'SignBlockName': 'Tianay Robinson', 'PO_EMAI': 'trobinso@nsf.gov', 'PO_PHON': '7032927859'}
Large-scale optimization problems arise in a great variety of important         scientific, engineering, and economic applications, and exhibit                 structures that allow solution via algorithms that possess a high               degree of parallelism.  Research will be continued in the development           of decomposition algorithms appropriate for the distributed solution of         such problems and in the implementation and testing of these methods on         a variety of parallel architectures including the multicomputers and            multiprocessors available at the Computer Sciences Department and those         available elsewhere via ARPANET.  Such algorithms have the large                granularity and low data transfer properties that are ideally suited to         parallel architectures.  Particular emphasis will be given to network           optimization problems, since a large proportion of the most difficult           real-world applications of mathematical programming fall into this              category, and since such problems also cover a broad spectrum of                mathematical classes (from linear to nonlinear, from convex to                  nonconvex, from deterministic to stochatic).  The development of                parallel algorithms for these problems will also require the                    development of scheduling and load-balancing techniques that will be            useful in the study of distributed techniques for other areas of large-         scale scientific computation.                                                                                                                                   The decomposition of problems to run simultaneously on multiple                 parallel processors is essential if these new architectures are to be           effectively used.
{'FirstName': 'Robert', 'LastName': 'Meyer', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert R Meyer', 'EmailAddress': 'rrm@cs.wisc.edu', 'NSF_ID': '000357784', 'StartDate': '08/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 N PARK ST STE 6301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_UEI_NUM': 'LCLSJAGTNZQ7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '2880', 'Text': 'SOFTWARE ENGINEERING AND LANGU'}
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