A performance/cost evaluation for a GPU-based drug discovery application on volunteer computing
Author
dc.contributor.author
Guerrero, Ginés D.
Author
dc.contributor.author
Imbernón, Baldomero
Author
dc.contributor.author
Pérez-Sánchez, Horacio
Author
dc.contributor.author
Sanz, Francisco
Author
dc.contributor.author
García, José M.
Author
dc.contributor.author
Cecilia, José M.
Admission date
dc.date.accessioned
2019-03-15T16:06:48Z
Available date
dc.date.available
2019-03-15T16:06:48Z
Publication date
dc.date.issued
2014
Cita de ítem
dc.identifier.citation
BioMed Research International, Volumen 2014,
Identifier
dc.identifier.issn
23146141
Identifier
dc.identifier.issn
23146133
Identifier
dc.identifier.other
10.1155/2014/474219
Identifier
dc.identifier.uri
https://repositorio.uchile.cl/handle/2250/166209
Abstract
dc.description.abstract
Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC) platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs) has democratized the use of HPC as they push desktop computers to cluster-level performance. Many applications within this field have been developed to leverage these powerful and low-cost architectures. However, these applications still need to scale to larger GPU-based systems to enable remarkable advances in the fields of healthcare, drug discovery, genome research, etc. The inclusion of GPUs in HPC systems exacerbates power and temperature issues, increasing the total cost of ownership (TCO). This paper explores the benefits of volunteer computing to scale bioinformatics applications as an alternative to own large GPU-based local infrastructures. We use as a benchmark a GPU-base