Cupseli

The Cupseli challenge aims to demonstrate that it is possible to run complex applications (particularly in the field of machine learning) on heterogeneous, distributed, and volatile resources, while achieving strong parallel efficiency and preserving both accuracy and confidentiality. Building on the combined expertise of hive and Inria in storage technologies illustrated in Alvearium (https://www.inria.fr/en/alvearium), this strategic partnership explores algorithmic and system solutions to optimize computation, memory, and communications, while ensuring security and fault tolerance. The work is organized around three axes: Frugality (adapting training and inference to limited and dynamic resources), Security and Confidentiality (protecting data and models through encryption, secure enclaves, and defenses against attacks), and Volatility (ensuring robustness and performance despite the unpredictable arrival and departure of resources). The shared goal is to offer a green and sovereign alternative to data centers, by leveraging already-existing resources for the benefit of AI and Big Data applications. This collaboration, anchored in this joint challenge, brings together researchers, PhD students, engineers, and postdocs, with large-scale experiments conducted on hive’s infrastructure.