Passcode: 862998

The rapidly increasing demand on computing power made by deep learning models in hyperscale data centers and supercomputers has spurred significant interest in developing novel hardware that can run large-scale artificial intelligence (AI) workloads more efficiently. Over the last several years, silicon photonics has emerged as a disruptive technology for next-generation interconnects and accelerators designed for high performance computing (HPC) and edge computing systems geared for AI and machine learning (ML) workloads. Furthermore, the heterogeneous integration of III-V compound semiconductors has opened the door to integrating lasers and semiconductor optical amplifiers at wafer-scale, enabling the scaling of the size, density, and complexity of silicon photonic integrated circuits (PICs). In this seminar, I will highlight key innovations and share future outlooks of our research on energy-efficient and scalable integrated photonics as the underlying foundation for next-generation heterogeneous computing architectures.