Packaging Matter: Extending Moore’s law with “re-aggregation”

By Sujit Sharan, Advanced Design and Technology Solutions, Intel Corporation

With the arrival of ChatGPT, Large Language Models (LLMs) have transformed AI into an interactive and accessible technology that recursively builds on its prior accomplishments, fueling a new gold rush era of applications. AI models have exploded in complexity and size, exerting demand pressure on both compute and memory. Over time, Moore’s law has yielded a roughly 2x increase in compute every 2 years, compared to the enormous 750x per year growth demand from the LLMs. Memory is an even trickier problem as it needs to address capacity, speed and cost of data transport. Packaging plays a pivotal role in this era, architecting bespoke solutions for a highly differentiated set of applications. We take a look at the role of disaggregation, chiplets and interconnects in enabling the future of AI and HPC and illustrate this with solutions that can help create unique functionality, performance, and cost while enabling reuse and modularity.