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Predictive Performance Modelling of Parallel Component Composition
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Predictive performance modelling of parallel component compositions
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Abstract: In this paper we discuss problems and solutions pertaining to the interaction of components representing parallel applications. We introduce the notion of a collective port which is an extension of the Common Component Architecture (CCA) ports and allows collective components representing parallel applications to interact as one entity. We further describe a class of translation components, which translate between the distributed data format used by one parallel implementation to that used by another. A well known example of such components is the MxN component which translates between data distributed on M processors to data distributed on N processors. We describe its implementation in Parallel Application Work Space (PAWS), as well as the data structures PAWS uses to support it. We also present a mechanism allowing the framework to invoke this component on the programmer's behalf whenever such translation is necessary, freeing the programmer from treating collective component interactions as a special case. In doing that we introduce framework-based, user-defined distributed type casts. Finally, we discuss our initial experiments in building optimized complex translation components out of atomic functionalities.