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Optimal Loop Parallelization

dc.contributor.authorAiken, Alexanderen_US
dc.contributor.authorNicolau, Alexandruen_US
dc.date.accessioned2007-04-23T17:24:50Z
dc.date.available2007-04-23T17:24:50Z
dc.date.issued1988-03en_US
dc.description.abstractParallelizing compilers promise to exploit the parallelism available in a given program, particularly parallelism that is too low-level or irregular to be expressed by hand in an algorithm. However, existing parallelization techniques do not handle loops in a satisfactory manner. Fine-grain (instruction level) parallelization, or compaction, captures irregular parallelism inside a loop body but does not exploit parallelism across loop iterations. Coarser methods, such as doacross [9], sacrifice irregular forms of parallelism in favor of pipelining iterations (software pipelining). Both of these approaches often yield suboptimal speedups even under the best conditions-when resources are plentiful and processors are synchronous. In this paper we present a new technique bridging the gap between fine-and coarse-grain loop parallelization, allowing the exploitation of parallelism inside and across loop iterations. Furthermore, we show that, given a loop and a set of dependencies between its statements, the execution schedule obtained by our transformation is time optimal: no transformation of the loop based on the given data-dependencies can yield a shorter running time for that loop.en_US
dc.format.extent1289049 bytes
dc.format.extent309424 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR88-905en_US
dc.identifier.urihttps://hdl.handle.net/1813/6745
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleOptimal Loop Parallelizationen_US
dc.typetechnical reporten_US

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