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服务器横向扩展互连技术 - UALink 超级节点和 CXL 内存池.pdf

上传人: 明**** 编号:1011884 2025-12-21 17页 2.75MB

1、VincentKong,Chief Ultra Link Architect-AlibabaServer Scale-Up Interconnect Technologies:UALink SuperNode and CXL Memory PoolServer Scale-Up Interconnect Technologies:UALink SuperNode and CXL Memory PoolVincentKong,Chief Ultra Link Architect-AlibabaOCP SPECIAL FOCUS:ARTIFICIAL INTELLIGENCE(AI)Cloud I

2、nfrastructure Needs Driven by ApplicationsNew application-driven deep collaboration and serverless,TCOAI-driven high performance GPU links and large memory requirementsCloudApplicationsGeneralComputingHeterogeneouscomputingAlibaba Server Scale Up SystemsLow latencyMemory semanticsLarge Pooling elast

3、icityData coherencyUltra-high bandwidth,extremely low latencyMemory semanticsMemory sharingThe heterogeneous is straight outALS(Accelerator Link System)CLS(CXL System)Scale Up Systems for CPUs and GPUsProtocolForm FactorTypical TrafficData PattenCommunication semanticsTypical BandwidthDomain SizeSca

4、le UpNvlink、UALinkGPU IOTP、EPHuge data size(Extremely latency-sensitive)Memory Semantics10TbpsSeveral RacksPCIe、CXLCPU IOMemory AccessCacheLine(Extremely latency-sensitive)Memory Semantics1TbpsSeveral RacksScale OutIB、UECPCIe CardDP、PPLarge data blockRDMA4800GbpsClusterCommon Need of Server System S

5、cale Up Fabricmemory semantics for GPU&CPULimited number of nodes,but ultra high performanceCacheLine coherent or IO coherent CXL is not only a memory hierarchy technology,it also enables tighter collaboration among multiple CPU nodes.Memory and storage are effectively tiered in Cloud Computing duri

6、ngpast 10 years,now SuperNodeServer is changing interconnect architectureParallel Algorithm Needb h 1 2 4 b h t 1 8EPEP DataData SizeSize ofof singlesingle OP:OP:TPTP DataData SizeSize ofof singlesingle OP:OP:Comparison of Data Transferred in EP/TP/PP/DP:Comparison of Data Transferred in EP/TP/PP/DP

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根据《》标记中的内容,全文主要内容概括如下: 1. **超链接架构**:阿里巴巴的Vincent Kong介绍了Ultra Link SuperNode和CXL Memory Pool技术,用于提升服务器扩展性能。 2. **性能需求**:AI应用驱动的高性能GPU链接和大量内存需求,以及低延迟、内存语义、大池弹性、数据一致性等。 3. **扩展与升级**:讨论了Scale Out和Scale Up网络性能,以及Nvlink、UALink、InfiniBand等协议在GPU和CPU扩展中的应用。 4. **超节点解决方案**:GPU超节点在LLM推理过程中的解码阶段显著提升了性能,例如8x8 GPU服务器比1x64 GPU服务器性能提升32.44%。 5. **CXL系统优势**:CXL系统在低延迟、原生内存语义支持、缓存一致性等方面优于RDMA系统,例如性能提升2.1倍。 6. **PolarDB 3-Tier架构**:基于CXL Memory Pool的PolarDB架构,通过CXL Memory Sharing实现性能提升,例如性能提升高达330%。 7. **开放生态系统**:阿里巴巴呼吁加入Alink和UALink生态系统,共同推动Scale-Up系统和协议的发展。
AI加速的秘密?" 云数据库的革新者?" 突破性能瓶颈?"
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