Visual MPI performance analysis using event flow graphs
Procedia Computer Science, 2015•Elsevier
Event flow graphs used in the context of performance monitoring combine the scalability and
low overhead of profiling methods with lossless information recording of tracing tools. In
other words, they capture statistics on the performance behavior of parallel applications
while pre-serving the temporal ordering of events. Event flow graphs require significantly
less storage than regular event traces and can still be used to recover the full ordered
sequence of events performed by the application. In this paper we explore the usage of …
low overhead of profiling methods with lossless information recording of tracing tools. In
other words, they capture statistics on the performance behavior of parallel applications
while pre-serving the temporal ordering of events. Event flow graphs require significantly
less storage than regular event traces and can still be used to recover the full ordered
sequence of events performed by the application. In this paper we explore the usage of …
Abstract
Event flow graphs used in the context of performance monitoring combine the scalability and low overhead of profiling methods with lossless information recording of tracing tools. In other words, they capture statistics on the performance behavior of parallel applications while pre- serving the temporal ordering of events. Event flow graphs require significantly less storage than regular event traces and can still be used to recover the full ordered sequence of events performed by the application.
In this paper we explore the usage of event flow graphs in the context of visual performance analysis. We show that graphs can be used to quickly spot performance problems, helping to better understand the behavior of an application. We demonstrate our performance analysis approach with MiniFE, a mini-application that mimics the key performance aspects of finite- element applications in High Performance Computing (HPC).
Elsevier
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