Advanced Packaging Road Map to 2030: Integrating Memory, Logic, and Systems for Artificial Intelligence

The exponential growth of artificial intelligence (AI) and high-performance computing (HPC) is driving a paradigm shift in semiconductor design, where advanced packaging has become a cornerstone for system-level scaling. This article presents a road map to 2030 for heterogeneous integration across logic, memory, photonics, and substrates, highlighting key innovations and challenges. Monolithic system on chips (SoCs) are being replaced by chiplet-based architectures and 3DIC stacking, enabled by TSVs, hybrid bonding, and backside power delivery networks (PDNs) to achieve finer interconnect pitches (<5 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i>m) and improved power integrity. Memory scaling is addressing the “memory wall” through high bandwidth memory (HBM) evolution—from HBM3E to HBM5—delivering bandwidths beyond 4 TB/s via ultradense stacking and direct metal–metal and hybrid bonding. Simultaneously, copackaged optics (CPO) is emerging as a transformative solution for data movement, integrating photonic engines with compute dies to enable >100-Tb/s bandwidth and superior energy efficiency. Interposers and substrates are expanding horizontally, scaling beyond 9× reticle sizes and transitioning toward glass cores for enhanced electrical and thermal performance, supported by panel-level packaging (PLP) for cost efficiency. Thermal management remains critical as AI workloads exceed multikilowatt power levels, necessitating innovations such as microfluidic cooling and advanced thermal interface materials (TIMs). Bonding technologies are evolving from thermal compression to hybrid bonding, leveraging fine-grain (FG) copper (Cu) and nitrogen-doped carbide (NDC) dielectrics for low-temperature high-density interconnects. Emerging approaches like silicon interconnect fabric (Si-IF) promise near-on-chip performance through package-less integration. Advanced packaging is no longer a mechanical necessity; it is a strategic enabler for scalable energy-efficient computing in the AI era.