Mango-IO: I/O Metrics Consistency Analysis

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

Performance tools are inseparable from complex HPC applications’ performance analysis and engineering life cycles. Due to the application’s complexity, various performance analysis tools are created to serve different analysis purposes and provide a deeper look at certain aspects of the applications. Although these tools might operate differently, having coherent information and consistent metrics across all tools is mandatory for ensuring analysis continuity. It is common for performance analysts to switch their usual performance tools due to various reasons and limitations. In this work, we look specifically at the I/O performance analysis tools landscape and introduce Mango-IO to verify the result consistencies between tools and provide tool-agnostic metrics calculation methods. Our analysis and case study provides lesson learned and guideline for ensuring measurement continuity and comparability.

Details

OriginalspracheEnglisch
TitelProceedings - 2023 IEEE International Conference on Cluster Computing Workshops and Posters, CLUSTER Workshops 2023
Herausgeber (Verlag)IEEE
Seiten18-24
Seitenumfang7
ISBN (elektronisch)9798350370621
ISBN (Print)979-8-3503-7063-8
PublikationsstatusVeröffentlicht - 31 Okt. 2023
Peer-Review-StatusJa

Workshop

Titel2023 IEEE International Conference on Cluster Computing Workshops
KurztitelCLUSTER Workshops 2023
Dauer31 Oktober 2023
Webseite
BekanntheitsgradInternationale Veranstaltung
OrtHilton Santa Fe Historic Plaza
StadtSanta Fe
LandUSA/Vereinigte Staaten

Externe IDs

Scopus 85179622959
Mendeley 87ca2d44-7a79-3686-8e09-174d86db0e65

Schlagworte

Schlagwörter

  • Measurement, Conferences, Switches, Cluster computing, Performance analysis, Complexity theory, Guidelines, Darshan, I/O, Recorder, Score-P, Vampir, consistency analysis, performance analysis tools