5 papers
Beyond Microservices: Testing Web-Scale RCA Methods on GPU-Driven LLM Workloads
Dominik Scheinert, Alexander Acker, Thorsten Wittkopp +6
Large language model (LLM) services have become an integral part of search, assistance, and decision-making applications. However, unlike traditional web or microservices, the hard…
Distributed LLM Pretraining During Renewable Curtailment Windows: A Feasibility Study
Philipp Wiesner, Soeren Becker, Brett Cornick +3
Training large language models (LLMs) requires substantial compute and energy. At the same time, renewable energy sources regularly produce more electricity than the grid can absor…
What happens when nanochat meets DiLoCo?
Alexander Acker, Soeren Becker, Sasho Nedelkoski +3
Although LLM training is typically centralized with high-bandwidth interconnects and large compute budgets, emerging methods target communication-constrained training in distribute…
Comparative Analysis of Large Language Models for the Machine-Assisted Resolution of User Intentions
Justus Flerlage, Alexander Acker, Odej Kao
Large Language Models (LLMs) have emerged as transformative tools for natural language understanding and user intent resolution, enabling tasks such as translation, summarization,…
Distributed Low-Communication Training with Decoupled Momentum Optimization
Sasho Nedelkoski, Alexander Acker, Odej Kao +2
The training of large models demands substantial computational resources, typically available only in data centers with high-bandwidth interconnects. However, reducing the reliance…