The 2nd Workshop on Software and Hardware Co-design of Deep Learning Systems in Future Architectures (SHDA) invites extended abstracts on new directions on co-design of machine learning systems in future architectures from academia, government, and industry. 

With the recent advancements in artificial intelligence, deep learning systems and applications have become a driving force in multiple transdisciplinary domains. This evolution has been supported by the rapid improvements of advanced processor, accelerator, memory, storage, interconnect and system architectures, including architectures based on future and emerging hardware (e.g., quantum, superconducting, photonic, neuromorphic). However, existing research is focused on hardware accelerators, deep learning systems and applications separately, but the co-design among them is largely underexplored. To develop high-performance deep learning systems on advanced accelerators, our workshop will focus on the following three important topics: 

1. adaptive deep learning model exploration and training for target inference devices based on customized user demands, 
2. joint optimization of deep learning model design with future accelerator architecture/compiler design, and 
3.  how to leverage state-of-the-art computational functionalities from advanced accelerators for application optimization. 

The scope of the workshop will not be limited to the above topics and the organizers will consider other abstracts that are closely related.

SHDA held in conjunction with ACM International Conference on Supercomputing (ICS), which will take place in Salt Lake City, Utah from June 8-11, 2025. This half-day workshop will be held on the afternoon of June 8, 2025 and will include sessions for 20-min extended abstract presentations, invited talks, and panel discussions. 

The workshop for the website can be found here: https://shda-workshop.github.io.

Submission Guidelines

Extended abstracts are at most two pages, formatted in a single-column layout with an 11-point font size on letter-sized paper, and peer-reviewed by the organizers.

Extended abstracts should be submitted through the EasyChair system.

Submission deadline: March 31, 2025 (AoE)

Author notification: April 7, 2025 (AoE)

Committees

Organizing and Program Committee

• Jong Choi (choij@ornl.gov)
• Shruti Kulkarni (kulkarnisr@ornl.gov)
• Seung-Hwan Lim (lims1@ornl.gov)
• Tong Shu (Tong.Shu@unt.edu)
• Elaine Wong (wongey@ornl.gov)

Contact

All questions about submissions can be emailed to any of the organizers.