4 citations · 4 across the 4 of their papers we have counts for
6 papers
Fetch Me If You Can: A Comprehensive Analysis of Fetch Metadata
Pedro Bernardo, Alex Ploner, Marco Squarcina +2
Effective server-side defenses against cross-site attacks depend on understanding the context in which browser requests are generated. However, servers often lack the information n…
An Engineering Journey Training Large Language Models at Scale on Alps: The Apertus Experience
Jonathan Coles, Stefano Schuppli, Lukas Drescher +20
Large Language Models (LLMs) have surged as a transformative technology for science and society, prompting governments worldwide to pursue sovereign AI capabilities that ensure dat…
Beyond Pre-Training: The Full Lifecycle of Foundation Models on HPC Systems
Dino Conciatore, Elia Oggian, Federico Da Forno +4
Large-scale pre-training of Foundational Models (FM) constitutes a computationally intensive first phase for enabling AI across diverse scientific and societal applications. This f…
Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
Project Apertus, Alejandro Hernández-Cano, Alexander Hägele +100
We present Apertus, a fully open suite of large language models (LLMs) designed to address two systemic shortcomings in today's open model ecosystem: data compliance and multilingu…
Evolving HPC services to enable ML workloads on HPE Cray EX
Stefano Schuppli, Fawzi Mohamed, Henrique Mendonça +10
The Alps Research Infrastructure leverages GH200 technology at scale, featuring 10,752 GPUs. Accessing Alps provides a significant computational advantage for researchers in Artifi…
GT4Py: High Performance Stencils for Weather and Climate Applications using Python
Enrique G. Paredes, Linus Groner, Stefano Ubbiali +8
All major weather and climate applications are currently developed using languages such as Fortran or C++. This is typical in the domain of high performance computing (HPC), where…