The post NVIDIA Introduces Spectrum-XGS Ethernet for Enhanced AI Data Center Connectivity appeared on BitcoinEthereumNews.com. Darius Baruo Sep 09, 2025 19:06 NVIDIA’s Spectrum-XGS Ethernet revolutionizes AI data center connectivity, enabling scale-across networking for large AI factories by overcoming latency and performance challenges. As artificial intelligence (AI) continues to evolve, the demand for more robust data center capabilities grows. NVIDIA has introduced Spectrum-XGS Ethernet technology, aimed at enhancing connectivity across distributed data centers to form large AI factories, according to NVIDIA’s blog. Understanding Scale-Across Networking Scale-across networking is a novel approach to AI compute fabric connectivity, distinct from traditional scale-up and scale-out methods. This technology allows multiple data centers of varying sizes and distances to function as a unified AI factory, providing the necessary performance for large-scale AI training and inference across geographically separated data centers. The Role of NVIDIA Spectrum-XGS Ethernet NVIDIA Spectrum-XGS Ethernet is an extension of the existing NVIDIA Spectrum-X Ethernet platform. It connects AI factories over long distances, potentially spanning cities or countries, by integrating hardware like Spectrum-X Ethernet switches and ConnectX-8 SuperNICs. The technology ensures high effective bandwidth and performance isolation, crucial for AI workloads that require synchronous network performance. Overcoming Latency Challenges Distance-aware algorithms play a crucial role in Spectrum-XGS Ethernet’s functionality. These algorithms manage the increased latency associated with data traveling over long distances, ensuring optimal GPU-to-GPU communication. Modified telemetry-based congestion control and adaptive routing algorithms are optimized to handle unique traffic patterns and maintain network performance without latency penalties. Performance Benefits and ROI In performance tests, NVIDIA Spectrum-XGS Ethernet demonstrated up to 1.9x higher NCCL all-reduce bandwidth compared to off-the-shelf Ethernet, particularly with larger message sizes common in AI training workloads. This improvement translates into faster job completion times, enhancing the efficiency of AI applications. Moreover, Spectrum-XGS Ethernet increases the return on investment (ROI) for AI factories by enabling data… The post NVIDIA Introduces Spectrum-XGS Ethernet for Enhanced AI Data Center Connectivity appeared on BitcoinEthereumNews.com. Darius Baruo Sep 09, 2025 19:06 NVIDIA’s Spectrum-XGS Ethernet revolutionizes AI data center connectivity, enabling scale-across networking for large AI factories by overcoming latency and performance challenges. As artificial intelligence (AI) continues to evolve, the demand for more robust data center capabilities grows. NVIDIA has introduced Spectrum-XGS Ethernet technology, aimed at enhancing connectivity across distributed data centers to form large AI factories, according to NVIDIA’s blog. Understanding Scale-Across Networking Scale-across networking is a novel approach to AI compute fabric connectivity, distinct from traditional scale-up and scale-out methods. This technology allows multiple data centers of varying sizes and distances to function as a unified AI factory, providing the necessary performance for large-scale AI training and inference across geographically separated data centers. The Role of NVIDIA Spectrum-XGS Ethernet NVIDIA Spectrum-XGS Ethernet is an extension of the existing NVIDIA Spectrum-X Ethernet platform. It connects AI factories over long distances, potentially spanning cities or countries, by integrating hardware like Spectrum-X Ethernet switches and ConnectX-8 SuperNICs. The technology ensures high effective bandwidth and performance isolation, crucial for AI workloads that require synchronous network performance. Overcoming Latency Challenges Distance-aware algorithms play a crucial role in Spectrum-XGS Ethernet’s functionality. These algorithms manage the increased latency associated with data traveling over long distances, ensuring optimal GPU-to-GPU communication. Modified telemetry-based congestion control and adaptive routing algorithms are optimized to handle unique traffic patterns and maintain network performance without latency penalties. Performance Benefits and ROI In performance tests, NVIDIA Spectrum-XGS Ethernet demonstrated up to 1.9x higher NCCL all-reduce bandwidth compared to off-the-shelf Ethernet, particularly with larger message sizes common in AI training workloads. This improvement translates into faster job completion times, enhancing the efficiency of AI applications. Moreover, Spectrum-XGS Ethernet increases the return on investment (ROI) for AI factories by enabling data…