E-waste challenges of generative artificial intelligence

P Wang, LY Zhang, A Tzachor, WQ Chen - Nature Computational …, 2024 - nature.com
Generative artificial intelligence (GAI) requires substantial computational resources for
model training and inference, but the electronic-waste (e-waste) implications of GAI and its …

ChatGPT in the age of generative AI and large language models: a concise survey

S Mohamadi, G Mujtaba, N Le, G Doretto… - arxiv preprint arxiv …, 2023 - arxiv.org
ChatGPT is a large language model (LLM) created by OpenAI that has been carefully
trained on a large amount of data. It has revolutionized the field of natural language …

Efficient training of large language models on distributed infrastructures: a survey

J Duan, S Zhang, Z Wang, L Jiang, W Qu, Q Hu… - arxiv preprint arxiv …, 2024 - arxiv.org
Large Language Models (LLMs) like GPT and LLaMA are revolutionizing the AI industry with
their sophisticated capabilities. Training these models requires vast GPU clusters and …

A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators

M Emani, S Foreman, V Sastry, Z **e, S Raskar… - arxiv preprint arxiv …, 2023 - arxiv.org
Artificial intelligence (AI) methods have become critical in scientific applications to help
accelerate scientific discovery. Large language models (LLMs) are being considered as a …

Comparative Study of Large Language Model Architectures on Frontier

J Yin, A Bose, G Cong, I Lyngaas, Q Anthony - arxiv preprint arxiv …, 2024 - arxiv.org
Large language models (LLMs) have garnered significant attention in both the AI community
and beyond. Among these, the Generative Pre-trained Transformer (GPT) has emerged as …

chatHPC: Empowering HPC users with large language models

J Yin, J Hines, E Herron, T Ghosal, H Liu… - The Journal of …, 2025 - Springer
The ever-growing number of pre-trained large language models (LLMs) across scientific
domains presents a challenge for application developers. While these models offer vast …

Tapi: Towards target-specific and adversarial prompt injection against code llms

Y Yang, H Yao, B Yang, Y He, Y Li, T Zhang… - arxiv preprint arxiv …, 2024 - arxiv.org
Recently, code-oriented large language models (Code LLMs) have been widely and
successfully used to simplify and facilitate code programming. With these tools, developers …

AI-coupled HPC Workflow Applications, Middleware and Performance

W Brewer, A Gainaru, F Suter, F Wang… - arxiv preprint arxiv …, 2024 - arxiv.org
AI integration is revolutionizing the landscape of HPC simulations, enhancing the
importance, use, and performance of AI-driven HPC workflows. This paper surveys the …

Toward a holistic performance evaluation of large language models across diverse ai accelerators

M Emani, S Foreman, V Sastry, Z **e… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
Artificial intelligence (AI) methods have become critical in scientific applications to help
accelerate scientific discovery. Large language models (LLMs) are being considered a …

Optimizing distributed training on frontier for large language models

S Dash, IR Lyngaas, J Yin, X Wang… - ISC High …, 2024 - ieeexplore.ieee.org
Large language models (LLMs) have demonstrated remarkable success as foundational
models, benefiting various downstream applications through fine-tuning. Loss scaling …