Jericho3-AI comes to market at a time when the use of AI is skyrocketing. According to a new forecast from
Fabrics based on Jericho3-AI will help network operators handle the ever-expanding workloads AI demands will present.
“The benchmark for AI networking is reducing the time and effort it takes to complete the training and inference of large-scale AI models,” said
AI workloads have unique characteristics such as a low number of large, long-lived flows, all starting concurrently upon completion of an AI computation cycle. The Jericho3-AI fabric provides the highest performance for these workloads with unique functionality designed specifically for AI workloads:
- Perfect load balancing equally sprays traffic over all links of the fabric, ensuring maximum network utilization under the highest network loads.
- Congestion-free operation with end-to-end traffic scheduling ensures no flow collisions and no jitter.
- Ultra-high radix uniquely allows the Jericho3-AI fabric to scale connectivity to 32,000 GPUs, each with 800Gbps, in a single cluster.
- Zero-Impact Failover functionality ensures sub-10ns automatic path convergence, resulting in no impact to job completion time.
Leveraging this unique functionality, the Jericho3-AI fabric provides at least 10 percent shorter job completion times versus alternative networking solutions for key AI benchmarks such as All-to-All. This performance improvement has a multiplicative effect on decreasing the cost of running AI workloads since it implies that expensive AI accelerators are used 10 percent more efficiently. The network, in effect, pays for itself.
The Jericho3-AI fabric offers 26 petabits per second of Ethernet bandwidth, almost four times the bandwidth of the previous generation, while simultaneously delivering 40 percent lower power per gigabit.
“Cloud operators will upgrade their AI infrastructure to address the massive growth in bandwidth, driven by a new generation of high-capacity GPUs and the emergence of large language models,” said
A unique feature of the Jericho3-AI fabric is that it provides the highest performance while also enabling the lowest total cost of ownership. This is achieved by virtue of attributes such as long-reach SerDes, distributed buffering, and advanced telemetry, all provided using industry-standard Ethernet. These factors provide a high degree of flexibility in network architectures and deployment options with the largest ecosystem of hardware and software providers.
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Michael KT Lee, Senior Vice President, R&D, Accton
“With the availability of Jericho3-AI, Accton can create the building blocks for the next generation AI clusters, pushing the scale boundaries once again, significantly increasing the radix and throughput of AI fabric and drastically improving the power efficiency for mega-scale GPU clusters.”
“The Arista 7800R3 running EOS is the premier AI spine supporting exponential growth of AI workloads and network traffic at petabit scale. We are excited to collaborate with Broadcom and drive the AI revolution using the innovative Ethernet-based cluster approach demonstrating groundbreaking performance in reducing the runtime of AI training and inference workloads.”
“The Jericho3-AI fabric architecture introduces a new way to build large-scale networks. Celestica is excited to see the next-generation building blocks of the merchant silicon-based architecture and the adoption of advanced AI training and inference clusters in support of open technologies.”
Ido Susan, Chief Executive Officer, DriveNets
“DriveNets has successfully partnered with Broadcom to deploy the world’s largest Core Routers based on Distributed Disaggregated Chassis (DDC) architecture. The Jericho3-AI fabric raises the bar for AI cluster scales. The unique properties of this fabric’s, perfect load-balancing and Zero-Impact Failover combined with DriveNets’
“Ufispace is dedicated to creating hardware required to support the success of Distributed Disaggregated Chassis architecture in Service-Provider Core and Edge networks. We are excited to leverage the Jericho3-AI fabric to expand solutions for high performance AI clusters, enabling the training of large AI models with the shortest job completion times.”
1 IDC, Worldwide Artificial Intelligence Spending Guide,
Source: Broadcom Inc.