Hauptseite > Publikationsdatenbank > Are Noise-Resilient Logical Timers Useful for Performance Analysis? > print |
001 | 1041737 | ||
005 | 20250804115251.0 | ||
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024 | 7 | _ | |a 10.1109/SCW63240.2024.00192 |2 doi |
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037 | _ | _ | |a FZJ-2025-02413 |
041 | _ | _ | |a English |
100 | 1 | _ | |a Corbin, Gregor |0 P:(DE-Juel1)188670 |b 0 |e Corresponding author |u fzj |
111 | 2 | _ | |a SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis |g SC24-W |c Atlanta |d 2024-11-17 - 2024-11-22 |w GA |
245 | _ | _ | |a Are Noise-Resilient Logical Timers Useful for Performance Analysis? |
260 | _ | _ | |c 2024 |b IEEE |
300 | _ | _ | |a 1519 - 1530 |
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520 | _ | _ | |a In modern HPC systems, performance measurements are often disturbed by noise. Because repeating measurements to increase confidence in their results is costly, alternative noise-resilient techniques are desirable. Therefore, we implement alogical clock, which does not rely on real-time measurements, in Score-P. We explore several methods to model computational work with the clock increment, counting OpenMP loop iterations, LLVM basic blocks/statements, or hardware counters. We demonstrate the strengths and weaknesses of using logical time stamps in a trace analysis workflow with Score-P and Scalasca, by evaluating the performanceproblems we can find in three MPI+OpenMP mini-apps. By design, logical measurementsreliably show algorithmic issues, such as load imbalance, but cannot capture external aspects of program execution, for example memory contention. In summary, logical-time based measurements are a specialized but valuable addition to theperformance analyst’s toolbox. |
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700 | 1 | _ | |a Daoud, Nour |0 P:(DE-Juel1)188664 |b 1 |
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700 | 1 | _ | |a Wolf, Felix |0 P:(DE-Juel1)132299 |b 4 |
770 | _ | _ | |z 979-8-3503-5554-3 |
773 | _ | _ | |a 10.1109/SCW63240.2024.00192 |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/1041737/files/Are_Noise-Resilient_Logical_Timers_Useful_for_Performance_Analysis.pdf |y Restricted |
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