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Performance monitoring of HPC applications offers opportunities for adaptive optimization based on dynamic performance behavior, unavailable in purely post-mortem performance views. However, a parallel performance monitoring system must have low overhead and high efficiency to make these opportunities tangible. The authors describe a scalable parallel performance monitor called TAUoverMRNet (ToM), created from the integration of the TAU performance system and the Multicast Reduction Network (MRNet). The integration is achieved through a plug-in architecture in TAU that allows selection of different transport substrates to offload online performance data.
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