Automated Methods for Runtime Performance Optimization for  Sparse and Irregular Numeric Applications
{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}
{'SignBlockName': 'Maxine Hynson', 'PO_EMAI': None, 'PO_PHON': None}
Scientific computational problems exhibit substantial data level                parallelism.  The PARTY run-time system is an attempt to obtain                 efficient parallel implementations for scientific computations,                 particularly those where the data dependencies are manifest only                at run-time.  This can preclude compiler based detection of                     certain types of parallelism.  The automated system is structured               as follows:  A high level language interface is employed in which               annotations are used to select an appropriate level of                          granularity.  A directed acyclic graph representation of the                    program is generated on which various aggregation techniques may                be employed in order to generate efficient schedules.  These                    schedules are then mapped onto the target machine.                                                                                                              Work clustering and scheduling heuristics are evaluated by 1)                   using sparse representation of regular problems with well studied               multiprocessor mappings, 2) comparing scheduling and clustering                 methods using a varied and realistic workload of sparse matrix                  problems, 3) generation, analysis and modeling of synthetic                     workloads.  The aggregation, mapping and parallel schedule                      execution methods and software modules developed in the context                 of the PARTY system are used to implement a system that schedules               and executes preconditioned Kryolov space sparse iterative                      algorithms and explicit PDE solution methods for non uniform                    meshes on the Encore Multimax, the Intel iPSC and Thinking                      Machine's CM-II.  Finally, a Fortran based interface to the PARTY               system will use annotated Fortran to facilitate transparent                     programmer access to PARTY.
{'FirstName': 'Joel', 'LastName': 'Saltz', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Joel H Saltz', 'EmailAddress': 'joel.saltz@stonybrookmedicine.edu', 'NSF_ID': '000325522', 'StartDate': '08/01/1989', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Yale University', 'CityName': 'NEW HAVEN', 'ZipCode': '065113572', 'PhoneNumber': '2037854689', 'StreetAddress': '150 MUNSON ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Connecticut', 'StateCode': 'CT', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'CT03', 'ORG_UEI_NUM': 'FL6GV84CKN57', 'ORG_LGL_BUS_NAME': 'YALE UNIV', 'ORG_PRNT_UEI_NUM': 'FL6GV84CKN57'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '4080', 'Text': 'ADVANCED COMP RESEARCH PROGRAM'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8819374.xml'}