Details of Intel’s unveiling of the world’s first OCI chiplet to enhance AI infrastructure and introduce optical I/O solutions

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Intel has announced the release of an industry-first fully integrated optical computing interconnect (OCI) chiplet, developed by the Integrated Photonic Solutions (IPS) group. This OCI chiplet is designed to support data transmission at high speeds over long distances using optical fiber. The chiplet can handle 64 channels of 32 gigabits per second (Gbps) data transmission in each direction, up to 100 meters. This innovation is aimed at addressing the increasing demand for energy-efficient, long-distance, and high-bandwidth solutions in data centers and high-performance computing applications.

The integration of optical computing interconnect technology with Intel CPUs is significant for the growth of AI infrastructure. As AI platforms based on large language models like GPT, Gemini, and Llama continue to expand, there is a need for scalable infrastructure and increased I/O bandwidth. By replacing electrical I/O with optical I/O, Intel aims to improve data transport capabilities and support larger processing unit architectures and clusters with better resource utilization.

The adoption of optical computing interconnect technology has the potential to revolutionize data transport in computing systems, enabling faster and more efficient communication between components. Intel plans to offer this OCI prototype to select customers for integration with their systems on chips (SoCs) to create optical I/O solutions.

Overall, Intel’s development of the industry’s first fully integrated optical computing interconnect chiplet represents a major advancement in AI infrastructure for data centers and high-performance computing applications. By embracing optical technology, Intel aims to improve data transmission speeds, reduce energy consumption, and support future scalability in computing architectures. This innovation is crucial for meeting the growing demands of AI platforms and ensuring efficient resource utilization in computing systems.

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