Alpha Networks 的 1.6T 创新技术赋能人工智能连接的未来.pdf

1、EMPOWERING the FUTURE of AI CONNECTIVITY withALPHA NETWORKS 1.6T INNOVATIONOctober 15,2025Steven OlenTechnical MarketingAlpha NetworksAlphas Core Competencies Challenges of Next-gen AI WorkloadsAGENDASolution:Alphas 1.6T Liquid-cooled SwitchInvitation to CollaborateAGENDA010203043CONNECTIVITY CHALLE

2、NGES IN AI/ML WORKLOADSBandwidthBottlenecksThermalManagementPowerConsumptionModularNetworkingAI training clustersrequire unprecedentedthroughput,leading tobandwidth bottlenecksIncreased processingpower results in higherthermal loads,exceeding air coolingcapabilitiesESG pressures demand greenerdata c

3、enters with lowerpower consumptionModular,opennetworking solutionsoffer operatorsflexibility acrossdiverse ecosystems4CHALLENGE:BANDWIDTHBandwidthBottlenecksAI training clustersrequire unprecedentedthroughput,leading tobandwidth bottlenecks AI training clusters involvetens of thousands ofconnected G

4、PUs and accelerators These clusters generate an immense amount of east-west traffic-GPUs communicating with each other Traditional switch fabrics werent designed for this type of traffic intensity When the network lags,GPUs sit idle Wasted compute time=wasted money The interconnect has become the ne

5、w bottleneckTHE AI ERA DEMANDS MORE5CHALLENGE:BANDWIDTH AI back-end networks will accelerate the migration to higher speeds Majority of switch ports are expected to be 1600 Gbps by 2027THE AI ERA DEMANDS MORE6CHALLENGE:THERMALThermalManagementIncreased processingpower results in higherthermal loads,

6、exceeding air coolingcapabilities Better performance higher power draw more heat In dense AI racks,thermal loads exceed what air cooling can realistically handle Data centers are reaching their limits in terms of airflow and cooling capacity Without innovation,thermal inefficiency becomes a ceiling