Why AI Data Centers Need Dynamic Optical Circuit Switching

With the rapid development of large language models, multimodal AI, and generative artificial intelligence, data centers are evolving from conventional data processing facilities into large-scale collaborative computing infrastructures. Thousands of GPUs and AI accelerators must exchange data through high-speed networks to support model training, parameter synchronization, and distributed computing work""s.

As a result, network performance is becoming an increasingly important factor in overall AI cluster efficiency. Traditional data center networks rely primarily on electrical switching to forward packets, using architectures such as Leaf-Spine to provide high-speed connectivity between servers. This technology is mature, flexible, and effective at handling diverse network traffic. However, as AI clusters expand and interconnect bandwidth increases, new challenges are emerging: how can data centers meet growing bandwidth demands while improving energy efficiency, reducing unnecessary conversion overhead, and adapting network connectivity to changing work""s?

These challenges are bringing optical switching back into the spotlight. In the AI computing era, network evolution is about more than increasing transmission speeds. It is also about making optical paths configurable to meet changing network demands. Optical Circuit Switching (OCS) offers a new approach to achieving this goal.

1. Why Are Growing AI Work""s Increasing Network Demands?
AI clusters have communication characteristics that differ from those of many conventional computing work""s. During large-scale model training, GPUs must not only perform local computations but also exchange data frequently with other computing nodes. For example, distributed training operations such as gradient synchronization, parameter exchange, and All-Reduce can generate substantial inter-node traffic. Insufficient network capacity or inefficient communication can affect the utilization of computing resources. As AI infrastructure continues to scale, data center networks face several important challenges.

1.1 Growing Bandwidth Requirements
As high-speed optical transceivers evolve from 400G to 800G and beyond, connectivity capacity within and between data centers continues to increase. However, higher transceiver speeds alone cannot solve every networking challenge. Switching architecture, link organization, congestion management, and topology design also influence end-to-end communication performance.

1.2 Increasing Power and Cooling Demands
AI data centers require substantial power and cooling resources to support computing, storage, and networking equipment. The power consumption of high-speed switching equipment, together with its associated cooling requirements, has become an important consideration in infrastructure planning. Beyond increasing bandwidth, reducing unnecessary signal-conversion and switching overhead is therefore becoming another area of focus in network optimization.

1.3 Changing Work""s Require More Flexible Connectivity
Different AI work""s may exhibit different communication patterns. Some tasks require sustained data exchange among large numbers of nodes, while others produce different traffic distributions. A network built around fixed physical connections may not always adapt efficiently to changing communication requirements. This does not mean traditional electrical switching can no longer meet AI data center requirements. Rather, it highlights an opportunity: adding a reconfigurable optical connectivity layer can provide greater flexibility in selected networking scenarios.

2. The Limitations of Traditional Electrical Switching: Why Consider Another Approach?
Traditional electrical switching is fundamental to modern data center networks. It processes packets and forwards them according to forwarding tables, supporting flexible routing, traffic management, and mature network operations. However, certain high-capacity connectivity scenarios offer opportunities for further optimization.

First, electrical switching equipment processes and forwards data in the electronic domain. As port speeds and switching capacities increase, the power consumption, cooling requirements, and equipment costs associated with switching chips and related circuitry require continued optimization. Second, in network architectures involving optical-electrical conversion, optical signals may be converted into electrical signals at certain nodes and converted back into optical signals for subsequent transmission. These conversion stages can introduce additional power consumption and processing overhead, depending on the equipment and network design. Finally, traditional network topologies are generally deployed around predefined connection structures. Although routing, traffic scheduling, and link management can adjust how traffic flows through the network, changing the underlying physical optical connections may require additional configuration or network changes. This is where OCS can provide another option. Rather than replacing electrical switching entirely, OCS introduces a different connectivity mechanism: establishing configurable optical paths at appropriate network layers so that physical optical connections can be reconfigured according to communication requirements.

3. How Does OCS Enable Dynamic Optical Path Reconfiguration?
Optical Circuit Switching (OCS) is a technology that establishes and switches optical paths directly in the optical domain. Unlike traditional electrical switching, which primarily processes individual data packets, OCS uses optical switching elements to establish direct connections between designated input and output ports. Once configured, optical signals pass through the switching fabric along the selected paths without requiring packet-level electronic processing within that fabric.

In a 3D MEMS-based OCS, for example, the system precisely controls the angles of micromirrors to direct incoming optical signals toward designated output ports, establishing the required optical connections. When network communication requirements change, the control system can reconfigure the connections between ports and adjust the optical paths accordingly.

Three Core Benefits of OCS
1. Reconfigurable Optical Paths for Greater Connectivity Flexibility
OCS can adjust optical connections between designated ports according to predefined configurations or higher-level control policies. For AI clusters with identifiable communication requirements, network designers can use traffic matrices and topology planning to map suitable high-capacity communication demands onto corresponding optical paths.

2. Reduced Conversion Overhead Within the Switching Fabric
Within an OCS optical switching fabric, signals can be switched directly in the optical domain, avoiding optical-electrical-optical (O-E-O) conversion that might otherwise be required at that switching stage. In suitable network architectures, this can help reduce conversion-related power consumption and processing overhead. However, OCS does not automatically eliminate all optical-electrical conversions across an end-to-end link. Overall energy savings depend on the system architecture, the equipment being replaced, optical path utilization, and the associated control and management mechanisms.

3. Greater Flexibility in Network Topology Optimization
OCS enables adjustments to physical optical connections, allowing network designers to move beyond relying exclusively on fixed connectivity relationships. When combined with appropriate control software and scheduling mechanisms, OCS can support network topology reconfiguration, optical resource al, and optimization for specific communication requirements. Its value therefore extends beyond switching optical signals: OCS provides an infrastructure layer for reorganizing optical connectivity as network needs evolve.

4. Which AI Data Center Applications Can Benefit from OCS?
OCS is not equally suitable for every traffic pattern or network layer. Its practical value depends on communication characteristics, optical circuit duration, reconfiguration frequency, and the overall deployment architecture.

Several application areas are worth considering.
4.1 Large-Scale AI Training Clusters
In large GPU clusters, certain nodes may have sustained, high-capacity communication requirements. If these communication relationships can be identified and mapped to suitable optical paths, OCS may help optimize connectivity between selected nodes or network partitions.

4.2 High-Performance Computing (HPC)
HPC clusters support scientific computing, simulation, and other computationally intensive work""s. For applications with predictable communication patterns, reconfigurable optical paths can provide additional options for network topology optimization.

4.3 Data Center Interconnect (DCI)
Between different facilities or data centers, OCS can be used to establish and adjust high-capacity optical connections, helping operators manage optical path resources according to actual requirements. Deployment must still account for transmission distance, optical power budgets, link protection, and network management requirements.

4.4 Infrastructure Requiring Flexible Optical Connectivity
OCS can also be used in certain test networks, dedicated computing networks, and optical transport systems to centrally manage connections between multiple ports and reduce the need for manual fiber reconnection. For these applications, deployment planning should consider port capacity, insertion loss, optical isolation, switching time, control interfaces, and fault-recovery mechanisms.

5. From 3D MEMS to High-Port-Count Matrices: The Evolution of OCS
As data centers place greater emphasis on optical path reconfiguration, OCS development involves more than increasing port count. Optical performance, system reliability, control capabilities, and manufacturing consistency are equally important.

Three-dimensional micro-electro-mechanical systems (3D MEMS) represent an important technology approach for optical switching. The basic principle involves adjusting microscopic mirrors to change the direction of optical signals and establish configurable paths between input and output ports. With appropriate optical design and control mechanisms, MEMS technology can support matrix optical switching systems with different port capacities.

For high-port-count OCS systems, engineering design must address several factors:
· Port capacity: Meet target connectivity requirements while allowing room for future expansion.
· Insertion loss: Control optical power loss along the switching path and maintain compliance with the end-to-end link budget.
· Optical isolation: Reduce unwanted optical leakage and crosstalk between paths.
· Switching time: Match reconfiguration performance to the requirements of the intended application.
· Long-term reliability: uate stability through appropriate environmental testing, switching endurance tests, and operational validation.
· Control and management: Support device configuration and maintenance, with integration into higher-level network control systems where required.
· Manufacturing consistency: Ensure that optical performance, assembly quality, and test results meet defined specifications across production units.

Together, these factors influence whether an OCS solution can progress from technical validation to practical deployment.

6. GLSUN 3D MEMS OCS: Optical Switching Solutions for AI Data Centers
To address the growing demand for high-speed connectivity and flexible optical path configuration in AI computing networks, GLSUN continues to advance its optical switching technology and product portfolio. GLSUN's OCS products use 3D MEMS optical switching technology and include matrix optical switching solutions with different port capacities, providing hardware options for data centers and other applications requiring configurable optical connectivity. Among these solutions, GLSUN's 128×128 OCS is designed for high-port-count optical switching requirements. It can be uated for network architectures that require a large number of configurable optical connections. Specific applications should be designed around network topology, port al, optical performance, and system interface requirements.

For AI data center deployments, GLSUN's OCS solutions offer several potential benefits.
Configurable optical connectivity
Establish optical connections between designated ports to provide the hardware foundation for networks requiring optical path reconfiguration.

Flexibility across different network architectures
Depending on application requirements, OCS can be uated alongside existing electrical switching networks and optical transport equipment, without treating optical switching as a complete replacement for conventional networking.

Integration with broader photonics manufacturing capabilities
GLSUN's business spans optical chips, optical components, modules, and system-level equipment. This broader presence across photonics technology and manufacturing provides an industrial foundation for continued optical switching development.

For data center operators, system integrators, and network architects uating OCS, considerations should extend beyond device specifications to include traffic suitability, optical performance validation, control-interface compatibility, production consistency, and long-term supply capabilities. GLSUN will continue developing its OCS products and photonics technologies to support the exploration of more flexible optical network architectures for AI infrastructure.

7. The Future of Data Center Networking: From Fixed Connectivity to Dynamic Reconfiguration

The continued growth of AI computing is encouraging data centers to reconsider how network connections are established and managed. Traditional electrical switching will continue to handle a wide range of packet-forwarding tasks, while OCS can provide reconfigurable optical connectivity in suitable scenarios. Together, these technologies offer network designers additional architectural options. However, the actual benefits of OCS cannot be determined by port count or switching capability alone. Traffic characteristics, network topology, optical performance, scheduling strategies, and operational requirements must all be considered to determine whether optical path reconfiguration delivers meaningful system-level value. The future of data center networking will not be defined solely by higher transmission speeds. It will also depend on how effectively network connectivity can be aligned with computing work""s. GLSUN will continue to focus on optical switching and photonics innovation, advancing 3D MEMS OCS solutions to help build more flexible and scalable optical networks for the evolving AI computing infrastructure.