How does the 3.2Tbps AI DCI Superhighway benefit AI training and inference?

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The 3.2Tbps AI DCI Superhighway enhances AI training and inference by enabling efficient scaling and synchronisation of operations across data centres.

The 3.2Tbps AI DCI Superhighway facilitates the efficient scaling of AI training and inference operations for infrastructure providers. Its high bandwidth and ultra-low latency capability ensure that thousands of Graphics Processing Units (GPUs) spread across different data centres can operate in sync. This synchronisation significantly reduces delays in data transmission, thereby lowering the time and cost associated with compute-intensive tasks. This advanced network infrastructure is designed to meet the demands of next-generation AI workloads, which are increasingly exceeding the capacity of individual facilities.
Enhanced Synchronisation of GPU Operations

The core benefit of the 3.2Tbps AI DCI Superhighway lies in its ability to maintain synchronisation among a vast number of GPUs. By minimising data transmission delays, it allows for thousands of GPUs, distributed across multiple data centres, to work together effectively. This coordinated operation is crucial for complex AI tasks that require massive parallel processing power.
Reduction in Compute Time and Cost

The reduction in delays in data transmission directly translates to a decrease in the overall time and cost required for AI compute operations. When data can be moved and processed with minimal latency, the efficiency of both training AI models and performing inference tasks is greatly improved. This is particularly important for AI infrastructure providers who need to optimise their resource utilisation and service delivery.
Support for Advanced Industry Standards and Technology

The Superhighway supports advanced industry standards such as Remote Direct Memory Access (RDMA), RDMA Over Converged Ethernet (RoCEv2), Multipath Reliable Connection (MRC), and Ultra-Ethernet Transport. It also utilises hollow core fibre technology, planned between Lok Ma Chau Loop and Tseung Kwan O, which is designed to achieve approximately 30% lower latency compared to traditional fibre optic cables. These technological advancements contribute to the network's overall performance and efficiency.

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How does the 3.2Tbps AI DCI Superhighway benefit AI training and inference?

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