Details

Autor(en) / Beteiligte

• Alor-Hernández, Giner
• Mejía-Miranda, Jezreel
• Álvarez-Rodríguez, José María

Titel

Scientific Programming Techniques and Algorithms for Data-Intensive Engineering Environments

Ist Teil von

• Scientific programming, 2018-01, Vol.2018, p.1-3

Ort / Verlag

New York: Hindawi

Erscheinungsjahr

2018

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• [...]digital technology fueled by ICT and ICT is currently embedded in any task, activity, and process that is done in any organization or even our daily life activities. More specifically, the availability of huge amounts of data that are continuously generated by persons, tools, sensors, and any other smart connected device requires new architectures to address the challenge of solving complex problems such as pattern identification, process optimization, discovery of interactions, knowledge inference, execution of large simulations, or machine cooperation. [...]the main objective of this special issue was to collect and consolidate innovative and high quality research contributions regarding scientific programing techniques and algorithms applied to the enhancement and improvement of engineering methods to develop real and sustainable data-intensive science and engineering environments. 2. [...]a paper entitled “A Heterogeneous System Based on Latent Semantic Analysis Using GPU and Multi-CPU” is by G. A. Leon-Paredes et al.