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Run-time parallelization and scheduling of loopsRun time methods are studied to automatically parallelize and schedule iterations of a do loop in certain cases, where compile-time information is inadequate. The methods presented involve execution time preprocessing of the loop. At compile-time, these methods set up the framework for performing a loop dependency analysis. At run time, wave fronts of concurrently executable loop iterations are identified. Using this wavefront information, loop iterations are reordered for increased parallelism. Symbolic transformation rules are used to produce: inspector procedures that perform execution time preprocessing and executors or transformed versions of source code loop structures. These transformed loop structures carry out the calculations planned in the inspector procedures. Performance results are presented from experiments conducted on the Encore Multimax. These results illustrate that run time reordering of loop indices can have a significant impact on performance. Furthermore, the overheads associated with this type of reordering are amortized when the loop is executed several times with the same dependency structure.
Document ID
19900017193
Acquisition Source
Legacy CDMS
Document Type
Preprint (Draft being sent to journal)
Authors
Saltz, Joel H. (NASA Langley Research Center Hampton, VA., United States)
Mirchandaney, Ravi (Yale Univ. New Haven, CT., United States)
Crowley, Kay (Yale Univ. New Haven, CT., United States)
Date Acquired
September 6, 2013
Publication Date
May 1, 1990
Subject Category
Mathematical And Computer Sciences (General)
Report/Patent Number
AD-A223323
NASA-CR-182039
ICASE-88-70-REV
NAS 1.26:182039
ICASE-90-34
Accession Number
90N26509
Funding Number(s)
CONTRACT_GRANT: NSF ASC-88-19374
CONTRACT_GRANT: N00014-86-K-0310
CONTRACT_GRANT: NAS1-18605
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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