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...
- 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