Recommended Optical Modules for AI Servers
Optical modules in AI servers are mainly used in GPU/TPU interconnects, rack-level networking, and large-scale data center connections to enable high-speed, low-latency communication.
Scale-Up Interconnects
In AI servers, scale-up interconnects connect GPUs, TPUs, or other accelerators within a single rack or tightly coupled cluster. Optical modules are increasingly replacing copper links in these environments to overcome bandwidth limitations and reduce latency. Co-packaged optics (CPO) and Optical Compute Interconnects (OCI) are deployed directly alongside switches and XPUs to support high-bandwidth, low-latency communication between accelerators, enabling efficient parallel computation and minimizing bottlenecks during model training .
Scale-Out Networking
For scale-out applications, optical modules connect multiple racks across hyperscale AI data centers. Copper cabling is insufficient for distances beyond a few meters, so optical interconnects are essential for maintaining high-speed data transfer between thousands of servers. Pluggable optical modules supporting 100 Gbps to 200 Gbps PAM4 signaling are commonly used, often incorporating components like Digital Signal Processors (DSPs), Transmit Optical Sub-Assemblies (TOSA), and Receive Optical Sub-Assemblies (ROSA) to ensure signal integrity and efficient transmission .
Data Center and Cluster-Level Applications
Optical modules also play a critical role in AI cluster networking, connecting GPU servers, storage systems, and switches. High-speed transceivers such as QSFP-DD and OSFP modules enable 400G and 800G connectivity, supporting massive east-west traffic generated during distributed AI training and inference. These modules convert electrical signals to optical signals for transmission over fiber, reducing power consumption, heat generation, and latency compared to copper cabling .
Key Advantages
- High bandwidth and low latency for GPU-to-GPU communication.
- Energy efficiency by reducing power consumption and heat.
- Scalability for connecting multiple racks and large AI clusters.
- Serviceability with pluggable modules that can be upgraded without downtime . In summary, optical modules are primarily deployed in accelerator interconnects within racks (scale-up), between racks in hyperscale data centers (scale-out), and in high-speed AI cluster networking to ensure efficient, low-latency, and energy-efficient data movement across AI servers and infrastructure .
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