About The Workshop
Training and deployment of 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.
Motivation
We are seeking innovative, evolutionary and revolutionary ideas around software and hardware architectures for training such challenging models and strive to present and discuss new approaches that may lead to alternative solutions.
Location
The workshop will be held in Buenos Aires, Argentina.
The workshop will be co-located with ISCA 2024.
Date: 30 June 2024
Call for papers
The workshop will present original works in areas such as (but not limited to):
- Workload Characterization
- Distributed Training
- Novel Networking and Interconnect Approaches
- Resilience of Large Training Runs
- Data Reduction Techniques
- Model Partitioning
- Data Formats and Precision
- Efficient Hardware and Competitive Accelerators
Scope of Papers
Authors can submit either 8-page full papers or up to 4-page short papers.
For the shart paper, out-of-the box ideas and position papers are especially encouraged.
Important Deadlines
All deadlines are at 11:59 PM AoE (Anywhere on Earth).
Paper Submission: 15 April 2024
22 April 2024 (Extended)
Accept Notification: 10 May 2024
Workshop Date: 30 June 2024
Event Schedule
ARC-LG workshop on Large Language Models and Graph Neural Networks
Schedule to be updated soon
ORGANIZATION
Program Co-Chairs
Avi Mendelson Technion
David Kaeli Northeastern University
Paolo Faraboschi Hewlett Packard Labs
Program Committee
Jose Luis Abellan University of Murcia
Rosa M Badia Barcelona Supercomputer Center
Chaim Baskin Technion
Jose Cano University of Glasgow
Freddy Gabbay Ruppin College
John Kim KAIST
Dejan S. Milojicic HPE
Alexandra Posoldova Sigma
Bin Ren William and Mary
Carole Jean Wu META
Jhibin Yu Shenzhen Institute of Technology
Publicity Chair
Pavana Prakash Hewlett Packard Labs
Web Chair
Kaustubh Shivdikar Northeastern University
Contact Us
For queries regarding submission