Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Alessio Orsino"'
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-17 (2024)
Abstract Large Language Models (LLMs) are characterized by their inherent memory inefficiency and compute-intensive nature, making them impractical to run on low-resource devices and hindering their applicability in edge AI contexts. To address this
Externí odkaz:
https://doaj.org/article/e0c389c6014e469fae6a3dc05f689b61
Autor:
Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino, Domenico Talia, Paolo Trunfio, Rosa M. Badia, Jorge Ejarque, Fernando Vázquez-Novoa
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-23 (2024)
Abstract The extensive use of HPC infrastructures and frameworks for running data-intensive applications has led to a growing interest in data partitioning techniques and strategies. In fact, application performance can be heavily affected by how dat
Externí odkaz:
https://doaj.org/article/4dc1829f814346e19d1d39032008d625
Publikováno v:
IEEE Access, Vol 11, Pp 38864-38874 (2023)
In recent years, there has been an increase in the use of edge-cloud continuum solutions to efficiently collect and analyze data generated by IoT devices. In this paper, we investigate to what extent these solutions can manage tasks related to urban
Externí odkaz:
https://doaj.org/article/15639bd8a56d4413a78dc116065e50d1
Autor:
Loris Belcastro, Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino, Domenico Talia, Paolo Trunfio
Publikováno v:
Journal of Big Data, Vol 9, Iss 1, Pp 1-50 (2022)
Abstract In the age of the Internet of Things and social media platforms, huge amounts of digital data are generated by and collected from many sources, including sensors, mobile devices, wearable trackers and security cameras. This data, commonly re
Externí odkaz:
https://doaj.org/article/047196eced554a8b93b24aea5a10a2d5
Publikováno v:
Future Internet, Vol 13, Iss 5, p 121 (2021)
Workflows are largely used to orchestrate complex sets of operations required to handle and process huge amounts of data. Parallel processing is often vital to reduce execution time when complex data-intensive workflows must be run efficiently, and a
Externí odkaz:
https://doaj.org/article/ce9e1a2c234e4a068e5b6dc9c5ecebbd
Publikováno v:
2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::08a107835fce4c7c82226a5528018b33
https://doi.org/10.1109/dasc/picom/cbdcom/cy55231.2022.9927824
https://doi.org/10.1109/dasc/picom/cbdcom/cy55231.2022.9927824
Publikováno v:
RTSI
Nowadays, the number of people who prefer to make online purchases on e-commerce platforms is constantly increasing. Online shopping turns out to be fast and cheap but it also involves some risks. In fact, it sometimes happens that a product, once re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8b9786d5ff59921644ec5fd1e34b38a9
https://doi.org/10.1109/rtsi50628.2021.9597230
https://doi.org/10.1109/rtsi50628.2021.9597230
Publikováno v:
Future Internet
Volume 13
Issue 5
Future Internet, Vol 13, Iss 121, p 121 (2021)
Volume 13
Issue 5
Future Internet, Vol 13, Iss 121, p 121 (2021)
Workflows are largely used to orchestrate complex sets of operations required to handle and process huge amounts of data. Parallel processing is often vital to reduce execution time when complex data-intensive workflows must be run efficiently, and a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ec6ebff76689fcd0706b0388c758f55