ARC-LG’ @ ISCA 2025

Workshop on New Approaches for Addressing the Computing Requirements of LLMs and GNNs (ARC-LG’) 2025
Co-located with ISCA 2025

Overview:
Training and deploying huge machine learning models, such as GPT, Llama, or large GNNs, require a vast amount of compute resources, power, storage, memory. The size of such models is growing exponentially, as is the training time and the resources required. The cost to train large foundation models has become prohibitive for everyone but very few large players. While the challenges are most visible in training, similar considerations apply to deploying and serving large foundation models for a large user base.
The proposed workshop aims to bring together AI/ML researchers, computer architects, and engineers working on a range of topics focused on training and serving large ML models. The workshop will provide a forum for presenting and exchanging new ideas and experiences in this area and to discuss and explore hardware/software techniques and tools to lower the significant barrier of entry in the computation requirements of AI foundation models.

Submissions:
Authors can submit either 8-page full papers or up to 4-page short papers. In the short paper format, out-of-the box ideas and position papers are especially encouraged.
See the website for submission details.

Topics:
The workshop will present original works in areas such as (but not inclusive to): workload characterization, inference serving at scale, distributed training, novel networking and interconnect approaches for large AI/ML workloads, addressing resilience of large training runs, data reduction techniques, better model partitioning, data formats and precision, efficient hardware and competitive accelerators.