General Information

The widespread adoption of mobile devices has revolutionized the way people interact with technology. Mobile platforms are becoming increasingly capable of running sophisticated artificial intelligence (AI) applications, including generative AI models. Generative AI, such as large language models and stable diffusion, has enabled remarkable advancements in various domains, including computer vision, natural language processing, and music generation. However, deploying and running these resource-intensive generative AI models efficiently on mobile platforms pose significant challenges.

This workshop aims to bring together researchers, practitioners, and industry experts to explore the architecture and system support required for effectively deploying generative AI models on mobile platforms. We will discuss the unique constraints of mobile devices, including limited computational resources, energy constraints, and storage limitations. Additionally, we will address the challenges of training and fine-tuning generative AI models on mobile devices while ensuring privacy and security.

Update! SAGE this year collaborates with IEEE Computer Architecture Letters (CAL) to publish top submissions in IEEE CAL. 

(Authors of top submissions will be notified of the procedure for submitting to IEEE CAL.)

Workshop Goals:

• Provide a platform for researchers and practitioners to share insights and experiences related to generative AI on mobile platforms.

• Identify the architectural/system-level challenges for deploying generative AI on mobile devices.

• Explore techniques and methodologies for efficient training, inference, and optimization of generative AI models on mobile platforms.

• Discuss privacy and security considerations specific to generative AI on mobile devices.

• Foster collaborations between academia and industry to accelerate the development and adoption of generative AI on mobile platforms.