Validating 1.6T Ethernet and Emulating Real AI Workloads
解决方案概述
This solution brief explores how the Keysight AresONE 1600GE platform enables full-stack validation of high-speed networks and next-generation AI data center infrastructure operating at 800GE and 1.6T Ethernet speeds. As AI clusters scale to tens of thousands of GPUs and adopt increasingly complex RoCEv2 and Remote Direct Memory Access (RDMA)-based traffic patterns, traditional network validation methods often lack the scale, realism, and visibility needed to identify performance issues, congestion behavior, and other bottlenecks before deployment.
The solution enables validation of 224G SerDes interfaces, Ethernet switches and NICs, AI switch fabrics, and large-scale distributed AI traffic patterns under realistic production conditions. It also supports analysis of Forward Error Correction (FEC) and Physical Coding Sublayer (PCS) behavior, along with congestion control mechanisms including Data Center Quantized Congestion Notification (DCQCN), Priority Flow Control (PFC), and Explicit Congestion Notification (ECN)
This paper highlights how network equipment manufacturers, hyperscalers, cloud providers, and AI infrastructure teams can accelerate validation workflows across multiple stages of deployment — from 1.6T Ethernet switch and NIC bring-up to end-to-end AI fabric benchmarking and real-world AI workload emulation. Integration with IxNetwork and Keysight AI Data Center Builder software enables deeper insight into latency, throughput, Queue Pair (QP) performance, collective communications, AI training workloads, and distributed GPU training efficiency to help reduce deployment risk and improve overall AI infrastructure performance.