Running scientific codes on amazon EC2: a performance analysis of five high-end instances

Amazon Web Services (AWS) is a well-known public Infrastructure-as-a-Service (IaaS) provider whose Elastic Computing Cloud (EC2) o ering includes some instances, known as cluster instances, aimed at High-Performance Computing (HPC) applications. In previous work, authors have shown that the scalabil...

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Autores principales: Expósito, Roberto R., Taboada, Guillermo L., Pardo, Xoán C., Touriño, Juan, Doallo, Ramón
Formato: Articulo
Lenguaje:Inglés
Publicado: 2013
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/34511
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Dec13-8.pdf
Aporte de:
id I19-R120-10915-34511
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
cloud computing
high performance computing
high throughput computing
Amazon EC2
OpenMP
spellingShingle Ciencias Informáticas
cloud computing
high performance computing
high throughput computing
Amazon EC2
OpenMP
Expósito, Roberto R.
Taboada, Guillermo L.
Pardo, Xoán C.
Touriño, Juan
Doallo, Ramón
Running scientific codes on amazon EC2: a performance analysis of five high-end instances
topic_facet Ciencias Informáticas
cloud computing
high performance computing
high throughput computing
Amazon EC2
OpenMP
description Amazon Web Services (AWS) is a well-known public Infrastructure-as-a-Service (IaaS) provider whose Elastic Computing Cloud (EC2) o ering includes some instances, known as cluster instances, aimed at High-Performance Computing (HPC) applications. In previous work, authors have shown that the scalability of HPC communication-intensive applications does not bene t from using higher computational power cluster instances as much as it could be expected. Cost analysis recommends using lower computational power cluster instances unless high memory requirements preclude their use. Moreover, it has been observed that scalability is very poor when more than one instance is used due to network virtualization overhead. Based on those results, this paper gives more insight into the performance of running scienti c applications on the Amazon EC2 platform evaluating ve (of which two have been recently released) of the higher computational power instances in terms of single instance performance, intra-VM (Virtual Machine) scalability and cost-e ciency. The evaluation has been carried out using both an HPC benchmark suite and a real High-Troughput Computing (HTC) application.
format Articulo
Articulo
author Expósito, Roberto R.
Taboada, Guillermo L.
Pardo, Xoán C.
Touriño, Juan
Doallo, Ramón
author_facet Expósito, Roberto R.
Taboada, Guillermo L.
Pardo, Xoán C.
Touriño, Juan
Doallo, Ramón
author_sort Expósito, Roberto R.
title Running scientific codes on amazon EC2: a performance analysis of five high-end instances
title_short Running scientific codes on amazon EC2: a performance analysis of five high-end instances
title_full Running scientific codes on amazon EC2: a performance analysis of five high-end instances
title_fullStr Running scientific codes on amazon EC2: a performance analysis of five high-end instances
title_full_unstemmed Running scientific codes on amazon EC2: a performance analysis of five high-end instances
title_sort running scientific codes on amazon ec2: a performance analysis of five high-end instances
publishDate 2013
url http://sedici.unlp.edu.ar/handle/10915/34511
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Dec13-8.pdf
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