Graduate Thesis Or Dissertation
 

Performance monitoring of parallel applications at large grain level

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/t435gh777

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  • This thesis is an attempt to create a methodology to analyze the performance of parallel applications on a wide variety of platforms and programming environments. First we determined the monitoring functions required to collect traces for accurate representation of the parallel application. We used the Extended Large Grain Data Flow (E L G D F) representation of an application to determine granularity and which monitoring functions should be inserted for sufficient feedback to application designer. The monitoring routines ( real time clock access procedures ) with a common interface were developed for the Sequent [superscript] TM multiprocessor machine and the C-Linda programming environment . We also developed an Execution Profile Analyzer( E PA ) for post-processing the traces. The E P A gives feedback to the mapping and scheduling ( TaskGrapher ) tool by providing actual performance data. These tools are being developed as a part of Parallel Programming Support Environment ( P P S E) research . Results indicate that when actual grain execution time is made available to scheduling tools, accurate projections of program behavior are obtained.
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file details YadavAnilKumar1990.pdf 2017-08-22 Öffentlich Herunterladen