218 citations · 448 across the 38 of their papers we have counts for
5 papers · 1 filter
SPIRT: A Fault-Tolerant and Reliable Peer-to-Peer Serverless ML Training Architecture
Amine Barrak, Mayssa Jaziri, Ranim Trabelsi +2
The advent of serverless computing has ushered in notable advancements in distributed machine learning, particularly within parameter server-based architectures. Yet, the integrati…
Exploring the Impact of Serverless Computing on Peer To Peer Training Machine Learning
Amine Barrak, Ranim Trabelsi, Fehmi Jaafar +1
The increasing demand for computational power in big data and machine learning has driven the development of distributed training methodologies. Among these, peer-to-peer (P2P) net…
Assessing Video Game Balance using Autonomous Agents
Cristiano Politowski, Fabio Petrillo, Ghizlane ElBoussaidi +2
As the complexity and scope of games increase, game testing, also called playtesting, becomes an essential activity to ensure the quality of video games. Yet, the manual, ad-hoc na…
An Exploratory Approach for Game Engine Architecture Recovery
Gabriel C. Ullmann, Yann-Gaël Guéhéneuc, Fabio Petrillo +2
Game engines provide video game developers with a wide range of fundamental subsystems for creating games, such as 2D/3D graphics rendering, input device management, and audio play…
Architecting Peer-to-Peer Serverless Distributed Machine Learning Training for Improved Fault Tolerance
Amine Barrak, Fabio Petrillo, Fehmi Jaafar
Distributed Machine Learning refers to the practice of training a model on multiple computers or devices that can be called nodes. Additionally, serverless computing is a new parad…