Abstract. As the complexity and diversity of computer hardware and the elaborateness of network technologies have made the implementation of portable and efficient algorithms more challenging, the need to understand application communication patterns has become increasingly relevant. This paper presents details of the design and evaluation of a communication-monitoring infrastructure developed in the Open MPI software stack that can expose a dynamically configurable level of detail concerning application communication patterns.

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Interconnection networks in parallel platforms can be made of thousands of nodes and hundreds of switches. The communication cost between tasks of a parallel application varies significantly with their actual location in such platforms. Topology-aware process mapping consists in matching the application communication pattern with the network topology to improve the communication cost by placing related tasks close on the hardware. We show that our Netloc tool for gathering network topology in a generic way can be combined with the state-of-the-art Scotch partitioner for computing topology-aware MPI process placement. Our experiments with a stencil application on a fat-tree machine show that we are able to significantly improve the runtime in the vast majority of cases.