Improving heterogenous storage performance in HPC Cloud systems using efficient storage algorithms informed by statistical models

Scientific applications are widely used to solve complex problems from different do- mains. These kinds of applications usually have demanding computational require- ments. Hence they must be executed in HPC clusters to guarantee a successful execution and find an optimal solution. In the last years...

Full description

Autores:
Marquez Franco, Jack Daniels
Tipo de recurso:
Doctoral thesis
Fecha de publicación:
2022
Institución:
Universidad Autónoma de Occidente
Repositorio:
RED: Repositorio Educativo Digital UAO
Idioma:
eng
OAI Identifier:
oai:red.uao.edu.co:10614/13693
Acceso en línea:
https://hdl.handle.net/10614/13693
https://red.uao.edu.co/
Palabra clave:
Doctorado en Ingeniería
Computación en la nube
Algoritmos genéticos
Computación evolutiva
Cloud computing
Evolutionary computation
HPC Cloud
EVT
Genetic algorithm
Heterogeneous storage
Rights
openAccess
License
Derechos reservados - Universidad Autónoma de Occidente, 2022