Contributo in atti di convegno, 2019, ENG, 10.1109/PDP.2019.00055

Parallel Computing in Deep Learning: bioinformatics case studies

V. Giansanti, S. Beretta, D. Cesini, D. D'Agostino, and I. Merelli

CNR-ITB, CNR-ITB, CNAF-INFN, CNR-IMATI, CNR-ITB

In the last two decades deep learning has attracted a lot of attention internationally, solving problems in different application domains and achieving results beyond expectations. For example it has been applied in bioinformatics, game playing, imaging processing, object detection, robotic and drug discovery. One of the main reasons for the incremented use of deep learning algorithms is the need to implement approaches for the analysis of the large amount of data produces in every field, bringing researchers to dedicate their work to deep learning development. One of the main topics discussed up today is the possibility to run the training of deep models in a parallel fashion, so to reduce the time otherwise needed to find the hyperparameters and to make the achievement of the result faster.

27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp. 329–333, Pavia (Italy), 13-15/02/2019

Keywords

deep learning, bioinformatic, parallel computing

CNR authors

Beretta Stefano, Giansanti Valentina, D Agostino Daniele, Merelli Ivan

CNR institutes

IMATI – Istituto di matematica applicata e tecnologie informatiche "Enrico Magenes", ITB – Istituto di tecnologie biomediche

ID: 399801

Year: 2019

Type: Contributo in atti di convegno

Creation: 2019-02-13 14:36:05.000

Last update: 2019-09-05 12:00:51.000

External links

OAI-PMH: Dublin Core

OAI-PMH: Mods

OAI-PMH: RDF

DOI: 10.1109/PDP.2019.00055

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:399801

DOI: 10.1109/PDP.2019.00055

ISI Web of Science (WOS): 000467257000046