Arzt, Peter ; Fischler, Yannic ; Lehr, Jan-Patrick ; Bischof, Christian
eds.: Sousa, Leonel ; Roma, Nuno ; Tomás, Pedro (2021)
Automatic Low-Overhead Load-Imbalance Detection in MPI Applications.
Euro-Par 2021: Parallel Processing. Virtual (Lisbon) (September 1–3, 2021)
doi: 10.1007/978-3-030-85665-6_2
Conference or Workshop Item
Abstract
Load imbalances are a major reason for efficiency loss in highly parallel applications. Hence, their identification is of high relevance in performance analysis and tuning. We present a low-overhead approach to automatically identify load-imbalanced regions and filter out irrelevant ones based on new selection heuristics in our PIRA tool for automatic instrumentation refinement for the Score-P measurement system. For the LULESH mini-app as well as the Ice-sheet and Sea-level System Model simulation package we, thus, correctly identify existing load imbalances while maintaining a runtime overhead of less than 10% for all but one input. Moreover, the traces generated are suitable for Scalasca's automatic trace analysis.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2021 |
| Editors: | Sousa, Leonel ; Roma, Nuno ; Tomás, Pedro |
| Creators: | Arzt, Peter ; Fischler, Yannic ; Lehr, Jan-Patrick ; Bischof, Christian |
| Type of entry: | Bibliographie |
| Title: | Automatic Low-Overhead Load-Imbalance Detection in MPI Applications |
| Language: | English |
| Date: | 25 August 2021 |
| Place of Publication: | Cham |
| Publisher: | Springer International Publishing |
| Book Title: | Euro-Par 2021: Parallel Processing |
| Series: | Lecture Notes in Computer Science |
| Series Volume: | 12820 |
| Event Title: | Euro-Par 2021: Parallel Processing |
| Event Location: | Virtual (Lisbon) |
| Event Dates: | September 1–3, 2021 |
| DOI: | 10.1007/978-3-030-85665-6_2 |
| Abstract: | Load imbalances are a major reason for efficiency loss in highly parallel applications. Hence, their identification is of high relevance in performance analysis and tuning. We present a low-overhead approach to automatically identify load-imbalanced regions and filter out irrelevant ones based on new selection heuristics in our PIRA tool for automatic instrumentation refinement for the Score-P measurement system. For the LULESH mini-app as well as the Ice-sheet and Sea-level System Model simulation package we, thus, correctly identify existing load imbalances while maintaining a runtime overhead of less than 10% for all but one input. Moreover, the traces generated are suitable for Scalasca's automatic trace analysis. |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Scientific Computing Zentrale Einrichtungen Zentrale Einrichtungen > University IT-Service and Computing Centre (HRZ) Zentrale Einrichtungen > University IT-Service and Computing Centre (HRZ) > Hochleistungsrechner |
| Date Deposited: | 20 Sep 2021 10:49 |
| Last Modified: | 20 Sep 2021 10:49 |
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