Industry First: UCIe Optical Chiplet Unveiled by Ayar Labs
Ayar Labs has unveiled the industry's first Universal Chiplet Interconnect Express (UCIe) optical interconnect chiplet, designed specifically to maximize AI infrastructure performance and efficiency while reducing latency and power consumption for large-scale AI workloads. This breakthrough will help address the increasing demands of advanced computing architectures, especially as AI systems continue to scale. By incorporating […] The post Industry First: UCIe Optical Chiplet Unveiled by Ayar Labs appeared first on Unite.AI.


Ayar Labs has unveiled the industry's first Universal Chiplet Interconnect Express (UCIe) optical interconnect chiplet, designed specifically to maximize AI infrastructure performance and efficiency while reducing latency and power consumption for large-scale AI workloads.
This breakthrough will help address the increasing demands of advanced computing architectures, especially as AI systems continue to scale. By incorporating a UCIe electrical interface, the new chiplet is designed to eliminate data bottlenecks while enabling seamless integration with chips from different vendors, fostering a more accessible and cost-effective ecosystem for adopting advanced optical technologies.
The chiplet, named TeraPHY™, achieves 8 Tbps bandwidth and is powered by Ayar Labs' 16-wavelength SuperNova™ light source. This optical interconnect technology aims to overcome the limitations of traditional copper interconnects, particularly for data-intensive AI applications.
“Optical interconnects are needed to solve power density challenges in scale-up AI fabrics,” said Mark Wade, CEO of Ayar Labs.
The integration with the UCIe standard is particularly significant as it allows chiplets from different manufacturers to work together seamlessly. This interoperability is critical for the future of chip design, which is increasingly moving toward multi-vendor, modular approaches.
The UCIe Standard: Creating an Open Chiplet Ecosystem
The UCIe Consortium, which developed the standard, aims to build “an open ecosystem of chiplets for on-package innovations.” Their Universal Chiplet Interconnect Express specification addresses industry demands for more customizable, package-level integration by combining high-performance die-to-die interconnect technology with multi-vendor interoperability.
“The advancement of the UCIe standard marks significant progress toward creating more integrated and efficient AI infrastructure thanks to an ecosystem of interoperable chiplets,” said Dr. Debendra Das Sharma, Chair of the UCIe Consortium.
The standard establishes a universal interconnect at the package level, enabling chip designers to mix and match components from different vendors to create more specialized and efficient systems. The UCIe Consortium recently announced its UCIe 2.0 Specification release, indicating the standard's continued development and refinement.
Industry Support and Implications
The announcement has garnered strong endorsements from major players in the semiconductor and AI industries, all members of the UCIe Consortium.
Mark Papermaster from AMD emphasized the importance of open standards: “The robust, open and vendor neutral chiplet ecosystem provided by UCIe is critical to meeting the challenge of scaling networking solutions to deliver on the full potential of AI. We're excited that Ayar Labs is one of the first deployments that leverages the UCIe platform to its full extent.”
This sentiment was echoed by Kevin Soukup from GlobalFoundries, who noted, “As the industry transitions to a chiplet-based approach to system partitioning, the UCIe interface for chiplet-to-chiplet communication is rapidly becoming a de facto standard. We are excited to see Ayar Labs demonstrating the UCIe standard over an optical interface, a pivotal technology for scale-up networks.”
Technical Advantages and Future Applications
The convergence of UCIe and optical interconnects represents a paradigm shift in computing architecture. By combining silicon photonics in a chiplet form factor with the UCIe standard, the technology allows GPUs and other accelerators to “communicate across a wide range of distances, from millimeters to kilometers, while effectively functioning as a single, giant GPU.”
The technology also facilitates Co-Packaged Optics (CPO), with multinational manufacturing company Jabil already showcasing a model featuring Ayar Labs' light sources capable of “up to a petabit per second of bi-directional bandwidth.” This approach promises greater compute density per rack, enhanced cooling efficiency, and support for hot-swap capability.
“Co-packaged optical (CPO) chiplets are set to transform the way we address data bottlenecks in large-scale AI computing,” said Lucas Tsai from Taiwan Semiconductor Manufacturing Company (TSMC). “The availability of UCIe optical chiplets will foster a strong ecosystem, ultimately driving both broader adoption and continued innovation across the industry.”
Transforming the Future of Computing
As AI workloads continue to grow in complexity and scale, the semiconductor industry is increasingly looking toward chiplet-based architectures as a more flexible and collaborative approach to chip design. Ayar Labs' introduction of the first UCIe optical chiplet addresses the bandwidth and power consumption challenges that have become bottlenecks for high-performance computing and AI workloads.
The combination of the open UCIe standard with advanced optical interconnect technology promises to revolutionize system-level integration and drive the future of scalable, efficient computing infrastructure, particularly for the demanding requirements of next-generation AI systems.
The strong industry support for this development indicates the potential for a rapidly expanding ecosystem of UCIe-compatible technologies, which could accelerate innovation across the semiconductor industry while making advanced optical interconnect solutions more widely available and cost-effective.
The post Industry First: UCIe Optical Chiplet Unveiled by Ayar Labs appeared first on Unite.AI.