Performance monitoring of throughput constrained dataflow programs executed on shared-memory multi-core architectures

Abstract : Because of physical limits, hardware designers have switched to parallel systems to exploit the still growing number of transistors per square millimeter of silicon. These parallel systems are made of several independent computing units. To benefit from these computing units, software must be changed. Existing sequential applications have to be split into independent tasks to be executed in parallel on the different computing units. To that end, many concurrent programming models have been proposed and are in use today. We focus in this thesis on the dataflow concurrent programming model. This work is about performance evaluation of dataflow programs on multicore architectures. We propose to extend dataflow programming models with the notion of throughput constraints and to take this information into account in the compilation tool chain to detect at runtime the throughput bottlenecks. The profiling results gathered during the execution are used both for off-line analyzes and to adapt the application during its execution. In the former case, the developer uses this information to know which part of the dataflow program should be optimized and to efficiently distribute the program on the computing units. In the later case, the profiling information is used by runtime adaptation mechanisms to distribute differently the work on the computing units. We give a particular focus on the profiling of the usage of the memory subsystem. The data exchange information provide by the programming model allows to efficiently used the memory subsystem of multicore architectures. Nevertheless, the complexity of modern memory systems doesn't allow to statically evaluate the impact of memory accesses on the global performances of the application. We propose to set up memory profiling dedicated to dataflow applications based on hardware profiling mechanisms.
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Manuel Selva. Performance monitoring of throughput constrained dataflow programs executed on shared-memory multi-core architectures. Performance [cs.PF]. INSA de Lyon, 2015. English. ⟨NNT : 2015ISAL0055⟩. ⟨tel-01264258v2⟩

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