Incremental Otimization in a Programming Environment
{'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'}
The recent abundance of interactive programming environments is                 significantly aiding the programmer of large software systems.  Response        times are enhanced by decreasing unnecessary recompilation, usually at          the expense of sophisticated program optimization.  This project                addresses the issue of providing an effective interactive environment           for developing highly optimized programs.  Two principal issues are to          be investigated.  (1) development of a recompilation system that, in            general, provides substantially better interactivity than existing              environments for highly optimized code but supports the same level of           optimization; (2) assessment of the most efficient recompilation                strategies under various scenarios of edits, program structure, and code        optimization.                                                                                                                                                   This project focuses on adapting the Rn Fortran programming environment         at Rice University to provide fine-grained partial recompilation without        sacrificing the ambitious (global and interprocedural) program                  optimization inherent of this environment.  The approach consists of            applying the incremental, intraprocedural optimization techniques               recently developed by the PI to the large-grained partial recompilation         system of Rn .  The performance of the fine-grained, partial                    recompilation system will be compared with the existing larger-grained          compiler of Rn  under different condition.  Ideally, the recompilation          system would be able to use this information to automatically determine         when it is more efficient to perform fine-grained recompilation analysis        or a total recompilation.  A foreseen contribution of this research is a        usable programming environment which offers precise recompilation               analyses coupled with the support of highly optimized programs.
{'FirstName': 'Lori', 'LastName': 'Pollock', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lori L Pollock', 'EmailAddress': 'pollock@udel.edu', 'NSF_ID': '000212323', 'StartDate': '07/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'William Marsh Rice University', 'CityName': 'Houston', 'ZipCode': '770051827', 'PhoneNumber': '7133484820', 'StreetAddress': '6100 MAIN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'TX09', 'ORG_UEI_NUM': 'K51LECU1G8N3', 'ORG_LGL_BUS_NAME': 'WILLIAM MARSH RICE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '2880', 'Text': 'SOFTWARE ENGINEERING AND LANGU'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1986&All=true', 'xml': '8618699.xml'}