Throughout the history of technological inflection points, the infrastructure “quadrangle” gets tested. A weak link, and any of the four variables will stress the system. When it comes to AI workloads, connectivity and performance matter. This is especially true given the immense volumes of data that must be processed to train large language models.
By contrast, in many ways the current enterprise AI hype cycle is a solution in search of many problems. Certainly, AI does and will provide great value to the enterprise. But today the enterprise side is not as clear as the consumer side, where customer needs have been well defined and the AI models required have been identified.
The Broadcom folks liken this process to making an automobile. It's like having an entire car ready for a customer, except for the engine. Rather than drop in any old engine, the manufacturer sits down with the driver to better understand how and where the vehicle will be used. Based on this understanding, the manufacturer installs an engine that will deliver the best performance at the lowest fuel consumption.
The company claims that among endpoint-scheduled devices, its Tomahawk 5 Ethernet network switch delivers twice the throughput of competing solutions, at 51.2 Tbps, while also delivering power efficiency and acceleration of AI and ML workloads through cognitive routing and advanced telemetry. Furthermore, Tomahawk 5 resource virtualization aims to improve security and enable the efficient utilization of shared infrastructure at scale.
While Broadcom makes good strides in CPO, it continues to also lead the market in the VCSEL space. Broadcom claims that it is offering the industry’s first optical interconnect designed for AI with its 200G VCSEL. It enables 1.6T optical links, facilitating terabit connectivity, and as a bonus supports both Ethernet and InfiniBand protocols. This dual compatibility is an important point to highlight, as it demonstrates Broadcom’s commitment to providing enterprises with interconnect flexibility.
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