釋放AI伺服器與機器學習潛力李永輝IBM大中華區硬體系統部首席技術官暨傑出工程師勢不可擋的AI市場“By 2020, 80% of Big Data and Analytics deployments will need distributed micro analytics and 40% of all business analytics software will incorporate prescriptive analytics built on cognitive computing functionality. Both of these trends require a dramatic increase in processing power that could be enabled by GPUs.” — IDC3DataComputeAlgorithms組成AI的三個元件各行各業的數據變換INCREASING DATA VARIETYSearch MarketingBehavioral TargetingDynamic FunnelsUser Generated ContentMobile WebSMS/MMSSentimentHD VideoSpeech To TextProduct/Service LogsSocial NetworkBusiness Data FeedsUser Click StreamSensorsInfotainment SystemsWearable DevicesCyberSecurity LogsConnectedVehiclesMachine DataIoT DataDynamic PricingPayment RecordPurchase DetailPurchase RecordSupport ContactsSegmentationOffer DetailsWeb LogsOffer HistoryA/B TestingBUSINESS PROCESSPETABYTESTERABYTESGIGABYTESEXABYTESZETTABYTESStreaming VideoNatural Language ProcessingWEBDIGITALAI釋放Data的價值Language UnderstandingLanguage TranslationSpeech TranscriptionFace RecognitionMachine ReasoningObject Detectionknowledge科技案例進展AI訓練的數據處理Define training taskPrepare training DataData Pre-processingDNN Model selectionConfigure the training hyper-parameterDNN Model TrainingStartPackage the new DNN model together with preprocessing into inference proc.DL training framework preparationApplication development with inference APITo build a team with deep learning expertise : 2 months ~ 1 year To prepare massive training data : ~ 10 man month(s)To train a new model : 1 hour ~ weekTo give a new inference result : < 1 secondCognitive System:Provide optimized SW + HW design, and tool chains to significantly enhance•Productivity•Performance•Time to market具備URLI的智能系統LearningDeep Learning / Machine LearningImage / Video / Voice RecognitionReasoningHigh Performance DataAnalytics Knowledge Representationand ReasoningUnderstandNatural Language Processing (NLP) Unstructured InformationManagementInteractiveText To Speech (TTS) / Speech to Text (STT) Question Answering TechnologyDataComputeAlgorithms組成AI的三個元件邁向 AI 之路Z14 伺服器LinuxONE 伺服器Power Systems UNIX 伺服器向外擴展伺服器（面向 NoSQL/Hadoop）CPU + GPU 伺服器（面向 AI/HPC）核心基礎架構下一代 AI 工作負載企業 AI 工作負載大資料工作負載任務關鍵工作負載IBM Systems 的解決方案專為顛覆當今最高級的資料應用而設計，其中不僅包括您目前所運行的任務關鍵應用，還包括下一代 AI 工作負載。彈性存儲伺服器(ESS)全新 POWER9 處理器專為認知業務而設計I/O Throughput Increases 61%@ 366GB/sEnergy Efficiency Improves 45%* & Workload Optimized FrequencyImproved Thread Performance with SMT8/4, Shorter PipelineAccelerator : PCIe Gen4, CAPI 2.0, OpenCAPI, NVLINK 2.0 & on-Chip SMP Interconnect & Off-Chip Accelerator EnablementOn-Chip AccelDDR4 InterfaceAccelerator SignalingAccelerator SignalingDDR4 InterfacePCIe SignalingSMP SignalingCoreL2L3 RegionCoreCoreL2L3 RegionCoreCoreL2L3 RegionCoreCoreL2L3 RegionCorePCIeCoreL2L3 RegionCoreCoreL2L3 RegionCoreCoreL2L3 RegionCoreCoreL2L3 RegionCoreCoreL2L3 RegionCoreCoreL2L3 RegionCoreCoreL2L3 RegionCoreCoreL2L3 RegionCore•14nm finFET 半導體處理器•80 億個電晶體、17 層金屬堆疊•120 MB eDRAM、12 x 20 路關聯區域•芯片上頻寬達 7 TB/sPOWER9 的創新加速技術CAPI 2.0EnhancementOpenCAPICollaboration• 一致性加速處理器介面• 計算加速（機器學習、視頻、生物資訊）• 存儲加速（記憶體中資料庫、存儲演算法）• 網絡加速（壓縮、加密）PCIe Gen 4Industry First• 2 倍輸送量• 後向相容• I/O 週邊設備連接• 實際 I/O 標準NVLINK 2.0 CPU-GPU 連接• 最大輸送量高達 300 GB/秒• CPU-GPU / GPU-GPU • 統一記憶體訪問• DL、HPC、GPU DB 的理想之選IBM與客戶、合作夥伴的POWER9創新案例BART SANO谷歌平臺副總裁谷歌對 IBM 能夠在最新POWER 技術研發上取得進展感到非常高興。POWER9 OpenCAPI 匯流排及大記憶體功能為穀歌資料中心的創新帶來了新的機會。IAN BUCKNVIDIA 總經理、副總裁加速計算IBM 致力於為客戶交付高性能的解決方案，例如適於NVIDIA® Tesla V100 GPU 和 NVLink 的 POWER9 解決方案，旨在説明客戶加速深度學習工作負載。OpenPOWER 2018 高峰會文章LimeLight 是一家致力於為客戶（如 BBC 和 Marvel Comics）提供各種各樣的高效工具，説明他們提升數位內容流處理水準的公司；該公司表示，OpenPOWER（以及基於 POWER9 的 PCIe Gen4）幫助他們克服了 PCIe Gen3 與其他伺服器一同使用時常常會出現的瓶頸，不僅加快了流處理速度，還縮短了緩衝時間。https://www.forbes.com/sites/patrickmoorhead/2018/03/19/headed-into-its-fifth-year-openpower-has-momentum-into-the-power9-generation/2/#74af40ef795aIBM POWER SYSTEMSAC922The best server of enterprise AIThe IBM Power Systems AC922 offers the fastest way to deploy deep learning frameworks and accelerated workloads – with enterprise class support.Up to 3.8X reduction in AI model training for deep learning frameworks1.8Xbetter performance of accelerated databases新一代的 NVLINK GPU 加速NVLinkDDR4NVL100 GB/sNVL100 GB/s100 GB/s100 GB/s170 GB/sV100 GPUV100 GPUV100 GPUIBM POWER9 CPUIBM POWER9™ 和 NVLink 2.0 有助於解決您在代碼方面的 PCI-E 瓶頸；相比參與測試的 x86 平臺的CUDA 主機設備頻寬，可將資料傳輸速度提升 5.6 倍。POWER9 是市場上唯一一款面向 NVLink 2.0 而推出的處理器，從 CPU 到 GPU 均是如此。Source - https://developer.ibm.com/linuxonpower/perfcol/perfcol-technical/世界上最快的超級電腦 IBM Power AC922• POWER9 CORAL 系統 – Summit：橡樹嶺國家實驗室 (ORNL) • 計算速度超過 150 Peta FLOPS，將會成為全球速度最快的超級電腦之一• 相比 Titan，僅需四分之一的節點，便可實現 5-10 倍的應用性能提升• ~3,500 x IBM Power AC922 (POWER9 + NVIDIA V100 GPU + Mellanox InfiniBand) + IBM ESS 存儲 + IBM Spectrum Computing HPC Software Stack17最新業企版 1.5PowerAI : Enterprise Software DistributionBinary Package of Major Deep Learning Frameworks with Enterprise SupportAI Vision* / DL Impact: Tools for Ease of Dev.Graphical tools to Enhance Data Scientist D...
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