The North American Workshop on Silicon Photonics for High-Performance Computing (SPHPC) will bring together experts in Silicon Photonics and in High-Performance Computing (HPC architects and experts, interconnect architects, HPC systems modeling, etc.) to discuss the state-of-the-art with Silicon Photonics based HPC interconnects and computing platforms (e.g., AI accelerators), and the main challenges that must be addressed to accelerate their development. It will consist of invited talks of the highest caliber from academia, industry, and government agencies as well as from different related disciplines. For SPHPC’23, we will focus on a special theme on Photonics for AI and AI for Photonics. In addition, SPHPC will host a student presentation session to invite students working in this area to present their projects at the workshop and receive feedback on their work. This is the event for meeting professionals in the field as well as exchanging and exploring new ideas. About SPHPC – https://www.engr.colostate.edu/SPHPC/ Silicon photonics has emerged as a promising solution to realize high-performance computing (HPC) systems required in the Big Data era. Having various applications in the domains of HPC, data centers, sensors and bio-sensing, aerospace, artificial intelligence (AI), etc., it has attracted researchers from academia and industries in different fields to explore various benefits and challenges of this technology. As an emerging area, it demands multidisciplinary collaborations and contributions, from material science and engineering, for realizing low-loss CMOS compatible components, to novel system architectures and software CAD and design tools to explore the design space of the resulting complex devices and systems. The North American Workshop on Silicon Photonics for High-Performance Computing (SPHPC) brings together experts from academia and industry working on silicon photonics and HPC (and other applications) to discuss the latest advances, remaining challenges, and research opportunities in this field. Co-sponsored by: Silicon Photonics high-performance computing (SPHPC), 29th IEEE International Symposium on High-Performance Computer Architecture (HPCA-29); Centre for Systems, Technologies and Applications for Radiofrequency and Communication (STARaCom); Agenda: https://www.engr.colostate.edu/SPHPC/program/ Time Speaker Topic Session 1 Chair: Mahdi Nikdast (Feb. 26th) 8:00 am – 8:20 am Volker J. Sorger George Washington University, USA Photonic Machine Intelligence: Tensor Core, Convolution Accelerator, Chip Packaging 8:20 am – 8:40 am Sean Pang University of Central Florida, USA Coherent Matrix Accelerator for Scalable Photonic Information Processing 8:40 am – 9:00 am Sudeep Pasricha Colorado State University, USA Cross-Layer Design of Machine Learning Accelerators with Silicon Photonics 9:00 am – 9:20 am Ajay Joshi, Boston University, USA Photonic Computing Architectures for AI: A Systems Perspective 9:20 am – 9:40 am Sebastien Le Beux Concordia University, Canada A Nanophotonic Interconnect based on Non-Volatile Phase Change Material 9:40 am – 9:50 am Kh Arif Shahriar PhD student, ECE Department, McGill University, Canada TBC 9:50 am – 10:00 am Daniel Hutama School of Electrical and Computer Engineering, University of Ottawa, Canada TBC Coffee break 10:00 am – 10:20 am Session 2 Chair: Kaveh Rahbardar Mojaver (Feb. 26th) 10:20 am – 10:40 am Bhavin Shastri Queens University, Canada Neuromorphic Silicon Photonics and Applications from Classical to Quantum 10:40 am – 11:00 am Emanuel Peinke 3e8, Canada A Scalable Optics Computing Approach 11:00 am – 11:20 am Nathan Youngblood University of Pittsburgh, USA Photonic Architectures for Computing In Memory Using Nonvolatile Optical Materials 11:20 am – 11:40 am Dan-Xia Xu National Research Council (NRC), Canada Optimization in the Non-Convex Design Space of Nanophotonic Components: Mitigation Strategies Using Machine Learning 11:40 am – 12:00 pm Dusan Gostimirovic McGill University, Canada Fabrication-Aware Design of Integrated Photonic Devices Using Convolutional Neural Networks 12:00 pm – 12:20 pm David Pan The University of Texas at Austin, USA Closing the Virtuous Cycle of Photonics for AI and AI for Photonics Hotel Bonaventure Montreal, 900 Rue De La Gauchetière O, Montréal, Quebec, Canada, H5A 1E4