Arzt, Peter ; Fischler, Yannic ; Lehr, Jan-Patrick ; Bischof, Christian
Hrsg.: Sousa, Leonel ; Roma, Nuno ; Tomás, Pedro (2021)
Automatic Low-Overhead Load-Imbalance Detection in MPI Applications.
Euro-Par 2021: Parallel Processing. Virtual (Lisbon) (01.09.2021-03.09.2021)
doi: 10.1007/978-3-030-85665-6_2
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (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.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2021 |
| Herausgeber: | Sousa, Leonel ; Roma, Nuno ; Tomás, Pedro |
| Autor(en): | Arzt, Peter ; Fischler, Yannic ; Lehr, Jan-Patrick ; Bischof, Christian |
| Art des Eintrags: | Bibliographie |
| Titel: | Automatic Low-Overhead Load-Imbalance Detection in MPI Applications |
| Sprache: | Englisch |
| Publikationsjahr: | 25 August 2021 |
| Ort: | Cham |
| Verlag: | Springer International Publishing |
| Buchtitel: | Euro-Par 2021: Parallel Processing |
| Reihe: | Lecture Notes in Computer Science |
| Band einer Reihe: | 12820 |
| Veranstaltungstitel: | Euro-Par 2021: Parallel Processing |
| Veranstaltungsort: | Virtual (Lisbon) |
| Veranstaltungsdatum: | 01.09.2021-03.09.2021 |
| DOI: | 10.1007/978-3-030-85665-6_2 |
| Kurzbeschreibung (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. |
| Freie Schlagworte: | SFB1194_Z-INF |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Scientific Computing Zentrale Einrichtungen Zentrale Einrichtungen > Hochschulrechenzentrum (HRZ) Zentrale Einrichtungen > Hochschulrechenzentrum (HRZ) > Hochleistungsrechner |
| Hinterlegungsdatum: | 20 Sep 2021 10:49 |
| Letzte Änderung: | 11 Dez 2023 15:16 |
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