IREN and BE Networks Collaborate to Optimize Large-Scale AI Infrastructure with NVIDIA DSX Air
In the realm of artificial intelligence infrastructure, precision and efficiency are paramount. Recently, BE Networks, renowned for its innovative networking and observability software solutions, has partnered with IREN Limited (NASDAQ IREN), a frontrunner in AI cloud infrastructure. This collaboration aims to leverage NVIDIA DSX Air to simulate and validate the network architecture that supports IREN's ambitious deployment of over 50,000 NVIDIA Blackwell Ultra GPUs.
The joint initiative allows both companies to utilize a digitally replicated version of IREN’s AI cloud environment, ensuring that potential issues can be identified and rectified before the substantial physical infrastructure is put in place. The ability to model large-scale GPU clusters through NVIDIA DSX Air provides an immense advantage, enabling teams to validate network topologies, test automation workflows, and rehearse changes that could significantly impact production systems.
Denis Skrinnikoff, CTO of IREN, emphasized the critical nature of AI cloud infrastructure at this scale, stating, “AI cloud infrastructure at this scale requires extreme precision. By combining NVIDIA DSX Air with BE Networks' automation expertise, we can validate critical design and operational decisions before deployment, reduce integration risk, and bring customer capacity online with greater confidence.”
BE Networks’ commitment to enhancing the deployment process is further supported by its Verity automation platform. This platform assists in translating validated designs into scalable deployment workflows, promoting operational efficiencies across all stages—from Day 0 design to Day 2 operations.
Amir Elbaz, the CEO and Founder of BE Networks, remarked on the challenges posed by large GPU clusters, stating that traditional lab environments often fall short in replicating the complexities of such deployments. “NVIDIA DSX Air gives us a virtual environment to prove the design, while Verity helps automate the path from validated intent to production-ready infrastructure,” he explained.
The ability to create digital twins of infrastructures via NVIDIA DSX Air not only accelerates the design validation process but also optimizes the deployment of software, turning weeks of validation into mere days. Gilad Shainer, Senior VP of Networking at NVIDIA, noted that this advancement is crucial for organizations looking to embrace the complexities of AI factories, which are among the most intricate systems built to date. “Simulation is becoming essential to deploying them at speed and scale,” said Shainer.
IREN's potent platform is structured on an extensive portfolio that includes grid-connected land and renewable power sources spread across North America, Europe, and the Asia-Pacific region. Meanwhile, BE Networks continues to push the boundaries of enterprise networking by reducing complexities in operational workflows and enhancing the scalability of open networking systems.
As AI technology evolves, the need for precision in infrastructure becomes even more critical. The cooperation between IREN and BE Networks not only embodies a significant step toward enhancing AI cloud capabilities with NVIDIA technologies but also sets a benchmark for future developments in the AI landscape. The goal remains clear: simulate first, validate at scale, automate the rollout, and deploy with confidence.
The joint initiative allows both companies to utilize a digitally replicated version of IREN’s AI cloud environment, ensuring that potential issues can be identified and rectified before the substantial physical infrastructure is put in place. The ability to model large-scale GPU clusters through NVIDIA DSX Air provides an immense advantage, enabling teams to validate network topologies, test automation workflows, and rehearse changes that could significantly impact production systems.
Denis Skrinnikoff, CTO of IREN, emphasized the critical nature of AI cloud infrastructure at this scale, stating, “AI cloud infrastructure at this scale requires extreme precision. By combining NVIDIA DSX Air with BE Networks' automation expertise, we can validate critical design and operational decisions before deployment, reduce integration risk, and bring customer capacity online with greater confidence.”
BE Networks’ commitment to enhancing the deployment process is further supported by its Verity automation platform. This platform assists in translating validated designs into scalable deployment workflows, promoting operational efficiencies across all stages—from Day 0 design to Day 2 operations.
Amir Elbaz, the CEO and Founder of BE Networks, remarked on the challenges posed by large GPU clusters, stating that traditional lab environments often fall short in replicating the complexities of such deployments. “NVIDIA DSX Air gives us a virtual environment to prove the design, while Verity helps automate the path from validated intent to production-ready infrastructure,” he explained.
The ability to create digital twins of infrastructures via NVIDIA DSX Air not only accelerates the design validation process but also optimizes the deployment of software, turning weeks of validation into mere days. Gilad Shainer, Senior VP of Networking at NVIDIA, noted that this advancement is crucial for organizations looking to embrace the complexities of AI factories, which are among the most intricate systems built to date. “Simulation is becoming essential to deploying them at speed and scale,” said Shainer.
IREN's potent platform is structured on an extensive portfolio that includes grid-connected land and renewable power sources spread across North America, Europe, and the Asia-Pacific region. Meanwhile, BE Networks continues to push the boundaries of enterprise networking by reducing complexities in operational workflows and enhancing the scalability of open networking systems.
As AI technology evolves, the need for precision in infrastructure becomes even more critical. The cooperation between IREN and BE Networks not only embodies a significant step toward enhancing AI cloud capabilities with NVIDIA technologies but also sets a benchmark for future developments in the AI landscape. The goal remains clear: simulate first, validate at scale, automate the rollout, and deploy with confidence.
Topics Consumer Technology）
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