Scalable Hardware Acceleration of Graph Processing with Photonic Interconnects

We need computing systems that can keep up with the exponential growth of data to enable the artificial intelligence-driven transformation of the modern world. Scalable graph processing systems that can handle graphs with trillions of edges present new challenges that require new ways of thinking about architecting computing systems. We show that the memory and interconnect requirements of large-scale graph processing systems mesh very well with the unique strengths of photonic interconnects, such as bandwidth density and the ability to provide high bandwidth, low latency, and low energy per bit across very long distances. These advantages of photonics can be synergized with emerging 3D and chiplet-based integration technology to create rackscale or warehouse-scale systems for high-speed predictive data analytics that can enable new applications in many disciplines.