Towards a model to estimate the reliability of large-scale hybrid supercomputers

 

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Detalles Bibliográficos
Autores: Rojas, Elvis, Meneses, Esteban, Jones, Terry, Maxwell, Don
Formato: ponencia
Fecha de Publicación:2020
Descripción:Supercomputers stand as a fundamental tool for developing our understanding of the universe. State-of-the-art scientific simulations, big data analyses, and machine learning executions require high performance computing platforms. Such infrastructures have been growing lately with the addition of thousands of newly designed components, calling their resiliency into question. It is crucial to solidify our knowledge on the way supercomputers fail. Other recent studies have highlighted the importance of characterizing failures on supercomputers. This paper aims at modelling component failures of a supercomputer based on Mixed Weibull distributions. The model is built using a real-life multiyear failure record from a leadership-class supercomputer. Using several key observations from the data, we designed an analytical model that is robust enough to represent each of the main components of supercom-puters, yet it is flexible enough to alter the composition of the machine and be able to predict resilience of future or hypothetical systems.
País:Repositorio UNA
Institución:Universidad Nacional de Costa Rica
Repositorio:Repositorio UNA
Lenguaje:Inglés
OAI Identifier:oai:null:11056/26728
Acceso en línea:http://hdl.handle.net/11056/26728
Palabra clave:RESILIENCIA
MODELADO DE FALLOS
ANÁLISIS DE FALLOS
TOLERANCIA A FALLOS
FAULT TOLERANCE
RESILIENCE
FAILURE ANALYSIS
FAILURE MODELLING