Photonic interconnect fabric supports future computing, AI
Offered as providing a “rack-on-chip interconnect,” Lightmatter Passage offers a fully-reconfigurable connection topology between chips, reducing the cost and complexity of building heterogeneous computing systems.
“Lightmatter is leading a necessary paradigm shift in computer architecture needed to power the next giant leaps in compute technology, while also reducing the negative impact on our planet of rapidly-growing state of the art, yet inefficient, compute and communications solutions,” says Nick Harris, co-founder and CEO at Lightmatter. “Modern compute workloads call for system-level performance. With Passage, we’ve created a photonic rack-on-chip solution capable of supporting the future of computing by enabling ultra-high bandwidth interconnection between different kinds of chips, and simultaneously reducing cost, complexity, and energy consumption.”
The solution packs forty switchable integrated photonic lanes into the same space that traditionally supports just one optical fiber. Planned to be the first in a multi-year roadmap of interconnects with increasing performance, Passage enables 1-Tbps dynamically reconfigurable interconnect across an array of 48 chips spanning 8 x 8 inches, with a maximum communication latency of 5 nanoseconds.
The result is higher bandwidth communication at lower energy and without the costly process of fiber-to-chip packaging. This architectural approach, says the company, provides a proven path to deliver chip-to-chip communications with 100-Tbps bandwidth – 100x that of currently available state-of-the-art photonic interconnect solutions.
The announcement of Passage follows on the company’s recent introduction of its artificial intelligence (AI) photonic computer chip: a general-purpose AI inference accelerator that uses light to compute and transport data—reducing heat & energy consumption and increasing computational performance by orders of magnitude. Passage, says the company, provides the capability to integrate this chip with a heterogeneous selection of other chips to enable a single wafer-scale, high-speed compute system.
The system directly addresses the urgent need for faster and more energy efficient (super)computers, capable of supporting next-generation AI inference and training workloads. The latest-and-greatest AI models require the capability of entire datacenters to train effectively, meaning single chip systems are no longer able to address the compute needs of current and future AI problems. Photonic-enabled systems, says the company, are the future for both high-performance computing and AI.
Related articles:
Optical processor speeds compute for next-gen AI
Google invests in photonic AI startup
Light-powered AI chip moves closer to market
Prototype optical AI accelerator chip debuts