Co-design for Heterogeneous Integration: A Failure Analysis Perspective

As scaling for CMOS transistors asymptotically approaches the end of Moore's Law, the need to push into 3D integration schemes to innovate capabilities is gaining significant traction. Further, rapid development of new semiconductor solutions, such as heterogeneous integration, has turned the semiconductor industry's consistent march towards next generation products into new arenas. In 2018, the Department of Energy Office of Science (DOE SC) released their "Basic Research Needs for Microelectronics," communicating a strong push towards "parallel but intimately networked efforts to create radically new capabilities,"1 which they have coined as "co-design." Advanced packaging and heterogeneous integration, particularly with mixed semiconductor materials (e.g., CMOS FPGAs & GaN RF amplifiers) is a realm ripe for applicability towards DOE SC's co-design call to action. In theory, development occurring at all scales across the semiconductor ecosystem, particularly across disciplines that are not traditionally adjacent, should significantly accelerate innovation. In reality, co-design requires a paradigm shift in approach, requiring not only interconnected parallel development. Further, accurate ground truth data during learning cycles is critical in order to effectively and efficiently communicate across disparate disciplines and advise design iterations across the microelectronics ecosystem. [GRAPHICS] This talk will outline three orthogonal facets towards co-design for HI: (1) on-going efforts towards development of materials characterization and failure analysis techniques to enable accurate evaluation of materials and heterogeneously integrated components, (2) development of artificial intelligence & machine learning algorithms for large scale, high throughput process development and characterization, and (3) development of capabilities for rapid communication and visualization of data across disparate disciplines.