EVENTO
Use of Machine Learning to Enable Performance and Energy Consumption Improvements in HPC Systems
Tipo de evento: Defesa de Dissertação de Mestrado
Scientific Computing has been indispensable for advances in several research domains because it offers a large capacity of computational resources that allow the execution of increasingly complex simulations. However, some areas still require greater computational capability to perform increasingly accurate simulations. To meet this demand make them feasible, High Performance Computing (HPC) systems are constantly evolving. In this sense, the development of new supercomputers and strategies that enable their development, such as the orchestration of computational resources in a more efficient way, in terms of performance and energy efficiency, has been sought. Among the challenges found to achieve these advances are the analysis and prediction of runtime and energy consumption for different classes of scientific applications executed in different computational architectures. Therefore, this work proposes a methodology for monitoring and analyzing scientific applications using performance counters, and the use of these as real data for Machine Learning (ML) techniques to understand the scientific applications, and how their performance characteristics regarding the use of computational resources. Still, ML is used as a technique for the development of models for characterization of the scientific applications and predictive models for runtime and energy consumption on the execution of an application in different architectures.Para assistir essa defesa acesse: https://us02web.zoom.us/j/87276484744?pwd=dml2T2FRUkJsVnYwbXcvQTU1NGdpQT09
Data Início: 29/09/2020 Hora: 14:00 Data Fim: 29/09/2020 Hora: 17:00
Local: LNCC - Laboratório Nacional de Computação Ciêntifica - Webinar
Aluno: Vinícius Prata Kloh - - LNCC
Orientador: Bruno Richard Schulze - Laboratório Nacional de Computação Científica - LNCC Mariza Ferro - Laboratório Nacional de Computação Científica - LNCC
Participante Banca Examinadora: Antônio Tadeu Azevedo Gomes - Laboratório Nacional de Computação Científica - LNCC Bruno Richard Schulze - Laboratório Nacional de Computação Científica - LNCC Luis Carlos Erpen de Bona - C3SL Centro de Computação Científica e Software Livre do Departamento de Informática da Universidade Federal de Paraná -
Suplente Banca Examinadora: Fábio Borges de Oliveira - Laboratório Nacional de Computação Científica - LNCC Mario Antonio Ribeiro Dantas - - UFJF
