Multi-Datacenter Training: Tackling AI Scaling Challenges Edge data centers are becoming a crucial part of the broader data center ecosystem. Beyond enabling localized compute for data sovereignty and reduced latency, they also contribute to exascale clusters. Advances in connectivity technology are ensuring that networks can keep pace with high-performance and accelerated computing demands. For optimal AI application performance, two key factors are essential: ✅ Ubiquitous compute ✅ Ubiquitous connectivity By interconnecting edge data centers, scalability challenges can be mitigated. This approach allows for flexible cost management, as workloads can be distributed dynamically across the network based on demand. A major hurdle remains power consumption, with accelerated compute racks requiring anywhere from 40kW to over 200kW. However, establishing a nationwide network enhances edge computing efficiency, ensuring AI workloads are processed seamlessly. #ai #edgecomputing #datacenters #hpc #exascale