Next-gen connectivity solutions for chiplet-based AI systems

This paper will explore the explosive growth in data consumption and how advancements in deep learning are driving transformative changes across industries. As AI applications generate unprecedented data volumes, memory bandwidth and latency challenges become critical hurdles. To address these challenges, innovations in chiplet-based architectures, 3D stacking, and heterogeneous computing are providing promising paths to overcome the limitations of conventional systems

The UCIe (Universal Chiplet Interconnect Express) die-to-die interface plays a crucial role in enabling efficient on-package pathways between various chiplets within the package. As the demand for higher performance and cost optimization continues to grow, designing UCIe D2D interfaces that cater to a diverse range of packaging options becomes essential. In this paper we will delve into the latest UCIe 2.0 standard and how it provides a playbook to enable 3D stacking of chiplets.

The potential for chiplet technology to be a transformational paradigm is now widely recognized. The cost, time-to-market, and power consumption benefits of chiplet-based solutions are compelling the industry toward integrating multiple dies in a single package in both 2.5D and 3D form factors. Technological evolution in stacking chips vertically using hybrid bonding enables very fine pitch connections between two dies. We will explore the challenges and technical tradeoffs required to build such a system-in-package design.

The chiplet approach, which combines dense logic and memory with the need for high-speed connectivity, significantly benefits custom silicon designed for AI. Chiplets offer the flexibility to create systems-in-package that balance cost, power, and performance for specific workloads without starting from scratch. Advanced packaging technologies, including 2.5D and 3D die integration, are driving the next generation of AI systems by enabling low-latency inter-die communication.