Abstract
We present AfterOMPT, a new trace-based tool for analyzing the execution of OpenMP applications using the OMPT interface to capture accurate information on loop partitioning, distribution of iteration spaces across workers, task scheduling, and synchronization events. In contrast to previous works that rely on specific, instrumented runtime libraries, our tool is able to collect information from any runtime implementing the OMPT interface. In order to visualize the information from the collected traces, we have extended the Aftermath performance analysis tool with appropriate renderers for OMPT events. We also propose an extension of the OMPT interface for the collection of more detailed information on scheduled OpenMP loops. Experimental results show a tracing overhead of under \(5\%\) for the majority of studied benchmarks, increasing more significantly for those with highly fine-grained workloads.
This work was supported by the grant EuroEXA H2020-754337. Antoniu Pop is funded by the RAEng University Research Fellowship. Igor Wodiany is supported by the Department of Computer Science Kilburn Scholarship and the University of Manchester Presidents Award.
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Notes
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Artifacts and sources available at: https://github.com/IgWod/ompt-loops-tracing.
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Partial verification of this changed dataset fails as it relies on pre-defined ranks for keys at specific locations, but full verification passes, so that we can assume that the algorithm executes correctly.
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The compilation error is caused by the potential bug in the unofficial C port of the benchmarks and does not appear in the official Fortran implementation.
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Wodiany, I., Drebes, A., Neill, R., Pop, A. (2020). AfterOMPT: An OMPT-Based Tool for Fine-Grained Tracing of Tasks and Loops. In: Milfeld, K., de Supinski, B., Koesterke, L., Klinkenberg, J. (eds) OpenMP: Portable Multi-Level Parallelism on Modern Systems. IWOMP 2020. Lecture Notes in Computer Science(), vol 12295. Springer, Cham. https://doi.org/10.1007/978-3-030-58144-2_11
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