Nvidia outlines plans for using light for communication between AI GPUs by 2026 — silicon photonics and co-packaged optics may become mandatory for next-gen AI data centers

Why CPO?

In large-scale AI clusters, thousands of GPUs must behave as one system, which introduces challenges in how these processors must be interconnected: instead of each rack having its own Tier-1 (Top-of-Rack) switch linked by short copper cables, the switches are moved to the end of the row to create a consistent, low-latency fabric across multiple racks. This relocation greatly extends the distance between servers and their first switch, which makes copper impractical at speeds like 800 Gb/s, so optical connections are required for nearly every server-to-switch and switch-to-switch link.

Using pluggable optical modules in this environment introduces clear limits: data signals in such designs leave the ASIC, travel across the board and connectors, and only then are converted to light. That method produces severe electrical loss, up to roughly 22 decibels on 200 Gb/s channels, which requires compensation that uses complex processing and increases per-port power consumption to 30W (which in turn calls for additional cooling and creates a point of potential failure), which becomes almost unbearable as the scale of AI deployments grow, according to Nvidia.

CPO sidesteps penalties of traditional pluggable optical modules by embedding the optical conversion engine alongside the switch ASIC, so instead of traveling over long electrical traces, the signal is coupled to fiber almost immediately. As a result, electrical loss is cut to 4 decibels, and per-port power consumption is reduced to 9W. Such a layout removes numerous components that could fail and greatly simplifies the implementation of optical interconnects.