针对 AI 工作负载优化的存储架构.pdf

1、1|2024 SNIA.All Rights Reserved.Storage Architecture Optimized for AI WorkloadsPresented by Paul McLeodProduct Director,StorageSupermicro2|2024 SNIA.All Rights Reserved.Storage Architecture Optimized for AI Workloads About Supermicro Storage challenges with AIOps and MLOps Moving beyond legacy stora

2、ge Solution approach Hardware innovation with EDSFF Summary3|2024 SNIA.All Rights Reserved.ABOUT SUPERMICRORevenueRevenue$14B+(FY2024 guidance)(FY2024 guidance)$7.1B(FY2023)$7.1B(FY2023)$5.2B(FY2022)$5.2B(FY2022)Worldwide Worldwide PresencePresence6M+Sq ft.Facilities Worldwide6M+Sq ft.Facilities Wor

3、ldwide1.Silicon Valley(HQ),2.Taiwan,3.The Netherlands,4.Malaysia and othersProductionProduction$18B/$18B/yryr Production Capacity(CY23)Production Capacity(CY23)Top 5 Largest Server System Provider Worldwide(IDC&Gartner 2022),1.3M units annuallyHuman Human Resource inResource in4 Campuses4 Campuses60

4、00+headcount Worldwide,50%Technical/R&DKey Growth Key Growth MatrixMatrix#1 in Generative AI and LLM Platforms500%+YoY Growth in Accel.Computing4|2024 SNIA.All Rights Reserved.AI/ML Implementation5|2024 SNIA.All Rights Reserved.Challenges for AI/ML Storage projectsLarge scale,rapid growthMixed data

5、sizes High concurrency of I/O PipelinesCentralized management Integration of emerging technologiesSource:WEKA6|2024 SNIA.All Rights Reserved.Source:SNIA7|2024 SNIA.All Rights Reserved.Source:SNIA8|2024 SNIA.All Rights Reserved.AI data pipeline:Multiple pipelines heating storageSource:WEKA9|2024 SNIA

6、.All Rights Reserved.9GPU Direct Storage(GDS)with WEKASupermicro+WEKA GDS provides RDMA with the GPU Memory Lowest latency for the AI Pipeline File-based single namespace for Flash and HDD Transparent file level access to S3 objects Scale-up from 138GB/s with an entry cluster*The performance number