Title:	DL4NLP: Deep Learning for Natural Language Processing
DNr:	Berzelius-2024-372
Project Type:	LiU Berzelius
Principal Investigator:	Marco Kuhlmann <marco.kuhlmann@liu.se>
Affiliation:	Linköpings universitet
Duration:	2024-10-01 – 2025-04-01
Classification:	10208
Homepage:	https://www.ida.liu.se/divisions/aiics/nlp/
Keywords:

Abstract

The Natural Language Processing (NLP) group at Linköping University is working on developing techniques for fine-tuning and analyzing large language models, such as GPT-4 and Llama3.1, a detailed introduction of which could be found in the next section. Given our recent utilization patterns and the influx of new members into our group, it's important to address our resource needs for the foreseeable future. We've nearly exhausted our current quota outside of summer months, and with numerous new members joining our group, our demand for resources is only going to increase. While it's difficult to predict the exact amount needed, we require an increased quota to 4950 hours per month. Although GPU usage dipped during the summer months, the start of new projects this semester, coupled with the expanding resource requirements within the NLP research community, underscores the necessity of increasing our current allocation. The trend of increasingly larger models and datasets in NLP research increases this demand even more so. Our experience with queuing issues, particularly during critical periods such as December and January conference deadlines, highlights the importance of having access to the requested GPU hours. Ensuring continuity in our research momentum and productivity depends on having access to adequate resources to meet our evolving needs.