The 2nd International Workshop on Deep Learning-Hardware Co-Design for Generative AI Acceleration

Bridging Theory and Applications in Modern Science

Co-Hosted by DAC 2025

Room 3003, Level 3, 9:00 AM (PDT) Sunday, June 22, 2025

Moscone West, San Francisco

About the Workshop

Building on the success of its inaugural edition, DCgAA 2025 delves deeper into the intersection of deep learning (DL) and hardware co-design, with a strong emphasis on real-world deployment and next-generation innovations in generative AI. This year, the workshop expands its focus to include key advancements such as multimodal fusion, real-time adaptive processing, and decentralized edge intelligence.

Recognizing the rise of foundation models, diffusion models, and large-scale generative systems, DCgAA 2025 prioritizes optimization for scalable, sustainable deployment. Topics will explore performance-energy tradeoffs and accessibility across diverse platforms, including edge devices, AR/VR systems, and IoT infrastructure—ensuring generative AI remains both powerful and practical.

The workshop will feature a rich mix of keynotes, paper sessions, interactive discussions, and new program elements. By uniting researchers, engineers, and innovators from academia and industry, DCgAA 2025 aims to push the frontier of hardware-aware generative AI and set new standards for scalable, efficient AI integration in the real world.

AI-Hardware Co-Design

Explore cutting-edge research at the intersection of deep learning and hardware acceleration to unlock new levels of efficiency and scalability.

Real-World Impact

Engage in discussions on deploying generative AI in diverse environments—from edge devices to immersive AR/VR platforms.

Collaborative Innovation

Connect with leading minds from academia and industry to shape the future of hardware-aware generative AI together.

Workshop Topics

The workshop will cover a broad range of topics to illuminate cutting-edge advancements and facilitate collaboration across domains, including:

Hardware-Aware Design for Generative Networks

Exploring network optimization under hardware constraints for scalable generative models.

Hardware Accelerators for Generative AI

specialized hardware to meet the unique demands of generative models.

Generative AI-Driven Computer Architecture Design

Harnessing generative models to inspire innovative hardware architectures.

Neural Network Pruning, Quantization, and Distillation

Optimizing generative models for greater efficiency and application diversity.

Theoretical Foundations of DeepLearning-Hardware Co-Design

Investigating principles and theories underpinning effective collaboration between DL and hardware.

Generative AI in Mobile and AR/VR Applications

Revolutionizing edge computing and immersive experiences in augmented and virtual reality.

Acceleration of Generative AI Processes

Enhancing real-time and practical deployment through advanced acceleration techniques.

Program Schedule

DCgAA 2025 introduces an enhanced program format featuring invited paper talks from DAC, interactive discussions, and panels. A key innovation for this year is the emphasis on dynamic and collaborative elements, such as interactive poster sessions and informal brainstorming opportunities during the coffee break.

June 22, 2025 (all times in PDT)

Opening Remark

9:00 AM

Keynote 1

David Z. Pan

9:00 AM - 9:40 AM

Keynote 2

Yizhou Sun

9:40 AM - 10:20 AM

Coffee Break & Poster Presentation

10:30 AM - 11:00 AM

Keynote 3

Yiran Chen

10:40 AM - 11:20 AM

Keynote 4

Peter A. Beerel

11:20 AM - 12:00 PM

Keynote 5

Tulika Mitra

12:00 PM - 12:40 PM

Closing Remark

12:40 PM

Each talk will be 35 minutes long, followed by a 5-minute Q&A session. The schedule is subject to change, and updates will be provided closer to the event date.