Adaptive Networking for Every AI Workload

iPronics ONE reconfigures in real time to meet the unique demands of scale-out, scale-up, and hybrid AI environments—keeping GPUs productive, networks resilient, and costs in check.

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Scale-out architectures

OCS between the layers
Spine replacement
Unblocking applications

AI applications depends on large networks where hardware failure is likely to happen. By adding OCS between layers, it can reroute around failures connecting with redundant equipment, reducing the GPU downtime.

Today’s data centers are optimized for uniform all-to-all traffic, but real AI workloads show structured, changing traffic patterns. Replacement of the spine layer by an OCS layer enables on-demand topology changes dynamically adjusting to actual traffic demand, reduce multi-hop forwarding and optimizes for elephant flows.

Scale-up architectures

Optically connected GPUs through NIC transceivers/CPO

In scale up applications, OCS enables more GPUs in the domains, and reconfiguration allowing  to adapt the topology to the needs of the AI job.

    We are disrupting data center management with a revolutionary optical networking engine
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