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Machine Learning and Artificial Intelligence

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Prezentace z konference Virtualization Forum 2019
Praha, 3.10.2019
Sál Pure Storage

Published in: Technology
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Machine Learning and Artificial Intelligence

  1. 1. ML + AI = FB Bogusz Błaszkiewicz
  2. 2. 2 © 2018 PURE STORAGE INC. PURE PROPRIETARY DATA FUELING THE 4TH INDUSTRIAL REVOLUTION 1st Revolution 1760-1820’s Steam Power Rural to Industrial 2nd Revolution 1870-1914 Electricity Industrial to Mass Production 3rd Revolution 1980-2010 PC Mass production to Digital 4th Revolution 2010-now Analytics & AI Digital to Intelligence
  3. 3. 3 EDA BACKUP RAPID RESTORE VIRTUAL MACHINES MISSION CRITICAL APPS & DATABASES ARCHIVE REAL-TIME ANALYTICS CLOUD BACKUP HPC BIGGEST SCALE AI / ML FlashBlade CONCURRENT FILE & OBJECT OBJECTENGINE //CLOUD OBJECTENGINE//A PERFORMANCE BACKUP OBJECT PERFORMANCE UNIFIED BLOCK AND VVOL Cloud Block Store FOR AWS BLOCK FILE VVOL VM VM VMVM FLASHBLADE SCIENTIFI C RESEARCH TIER 1 TIER 2 VMs & DB
  4. 4. FLASHBLADE THE INDUSTRY’S FIRST DATA HUB HIGH THROUGHPUT FILE & OBJECT SIMPLE, NATIVE SCALE-OUT MULTI- DIMENSIONAL PERFORMANCE DATA WAREHOUSE DATA LAKE STREAMING ANALYTICS AI CLUSTERBACKUP MASSIVELY PARALLEL TM FlashBlade is industry’s first data hub for storage infrastructure
  5. 5. 5 FLASHBLADEINDUSTRY’S FIRST DATA HUB PURPOSE-BUILT FOR MODERN DATA BLADE SCALE-OUT FABRIC Powerful, Elastic Data Processing & Storage Unit Massively Distributed Software for Limitless Scale Software-defined fabric that scales linearly with more data & clients BIG, FAST, SIMPLE Unique scale-out HW & SW design Up to 1PB, 1M IOPS, and 15 GB/s in each 4U chassis Multi-chassis scalability (up to 5) FILE + OBJECT Share data across NFS, Object S3, SMB, HTTP, REST. Ideal for HPC, data analytics, heavy computational, rapid restore, etc
  6. 6. 6 FLASHBLADE BLADES Intel XEON System-on-a-Chip Compute + Networking + Chipset Low-Power, Low-Cost Design 6 - 8x Full XEON Cores DRAM Memory Programmable Processors 1 x FPGA 2 x ARM Cores Elastic Fabric Connectors DirectFlash NAND 17TB or 52TB Runs distributed on all processors Integrated NV-RAM Super capacitor- backed DRAM write buffer PCIe Connectivity CPUs & Flash communicate via proprietary protocol over PCIe
  7. 7. 7 INTEGRATED NETWORKINGSOFTWARE-DEFINED NETWORKING 2x BROADCOM TRIDENT-II ETHERNET SWITCH ASICS Collapses three networks – frontend, backend, and control – into one high-performance fabric 8x 40Gb/s QSFP Connections into customer top-of-rack switches FlashBlade Chassis Up to 15 Blades 4RU Height N+2 Redundant, Heals in Place Blades Capacity & Performance DirectFlash NAND Embedded NVRAM
  8. 8. 8 Multi Chassis • 75 Blades • 5 Chassis • 16x 100GbE uplinks • Dedicated OOB management Ports • Linear Performance to 75GB/s and 7.5M IOPS* • Simple management – single data VIP • Single namespace • 2x Pure Storage FlashBlade eXternal Fabric Modules (XFMs)
  9. 9. 9 ANNOUNCING FLASHBLADE WITH 150 BLADES UNDER SINGLE NAMESPACE 2x CAPACITY WITH SAME SIMPLICITY DIRECTED AVAILABILITY
  10. 10. 10 FLASHBLADE ARCHITECTURE STORAGE UNIT NVRAMFLASH STORAGE UNIT NVRAMFLASH STORAGE UNIT NVRAMFLASH NETWORK SWITCHNETWORK SWITCH … Distributed Control Distribute all data, metadata, and control across stateless authorities on blades. Distributed Storage Distribute all persistent data across all blades, including high-frequency updates in NVRAM and bulk data in N+2 erasure-coded flash. PROTOCOLSPROTOCOLS PROTOCOLS
  11. 11. 11 RESULTS: LINEAR SCALE512K IO sizes, 16 load generators (48 core CPU’s each with 2x10GbE), 256 Containers total, NFSv3 7 8 9 10 11 12 13 14 15 Read 7,4 8,4 9,3 10,3 11,2 12,2 13,1 14,1 15,0 Write 2,2 2,5 2,8 3,1 3,4 3,6 3,9 4,2 4,5 0,0 1,5 3,0 4,5 6,0 7,5 9,0 10,5 12,0 13,5 15,0 GByte/Sec Blades Blades
  12. 12. 12 EVERGREEN STORAGE ALL-INCLUSIVE SOFTWARE FLAT AND FAIR MAINTENANCE CAPACITY CONSOLIDATION LYS GUARANTEE DIFFERENTIATED BUSINESS MODEL 8TB 52TB
  13. 13. 13 AI DATA HUB POWERS REAL-WORLD AI DELIVERS MULTI-DIMENSIONAL PERFORMANCE FOR END-TO-END AI PIPELINE INGEST CLEAN, LABEL, RESIZE EXPLORE TRAIN MODEL CPU Servers GPU Server DEPLOY MODEL GPU Production Cluster
  14. 14. 14 SHARE MORE DATA WTH FLASHBLADE BUILT TO DELIVER PERFORMANCE, SIMPLICITY FOR ANY DATA PIPELINE DATA WAREHOUSE DATA LAKE STREAMING ANALYTICS AI CLUSTER DATA HUB DEV CLUSTERRAPID RESTORE
  15. 15. 15 AIRI NVIDIA® DGX-1™ | 4x DGX-1 Systems | 4 PFLOPS of DL Performance PURE FLASHBLADE™ | 15x 17TB Blades | 1.5M IOPS CISCO or ARISTA | 2x 100Gb Ethernet Switches with RDMA NVIDIA GPU CLOUD DEEP LEARNING STACK | NVIDIA Optimized Frameworks AIRI SCALING TOOLKIT | Multi-node Training Made Simple THE INDUSTRY’S FIRSTCOMPLETE AI-READY INFRASTRUCTURE HARDWARE SOFTWARE AIRI “mini” NVIDIA® DGX-1™ | 2x DGX-1 Systems | 2 PFLOPS of DL Performance PURE FLASHBLADE™ | 7x 17TB Blades | 700K IOPS CISCO or ARISTA | 2x 100Gb Ethernet Switches with RDMA
  16. 16. TECHNOLOGY STACK AI-AT-SCALE MADE SIMPLE MULTI-NODE TRAINING AIRI Scaling Toolkit NVIDIA OPTIMIZED DEEP LEARNING FRAMEWORKS CONTAINERIZATION GPU-optimized Docker SCALE-OUT GPU COMPUTE NVIDIA DGX-1 with Tesla V100 GPUs SCALE-OUT FILE & OBJECT PROTOCOLS Pure Storage Purity//FB SCALE-OUT FLASH STORAGE Pure Storage FlashBlade . . . . . . AIRI TECHNOLOGY STACK INCLUDES NVIDIA GPU CLOUD DL STACK & SCALING TOOLKIT
  17. 17. © 2018 PURE STORAGE INC. PURE PROPRIETARY17 “The combination of NVIDIA DGX-1 and Pure Storage FlashBlade is helping us reduce training times, which means IT investment is better utilized and data scientists are more productive and ultimately happier.” Benny Nilsson Manager of Deep Learning at Zenuity • Zenuity, Volvo Cars and Autoliv joint venture, to develop autonomous vehicle software • Chose DGX-1 & FlashBlade because data scientist productivity is most important • FlashBlade, only system of 10 alternatives to withstand rigorous DL benchmarks • Expects to deploy more DGX systems to meet growing AI needs
  18. 18. 18 DELIVERING DATA THROUGHPUT FOR AI Deep Learning Needs Maximum Read Performance, Mostly Small Files, To Keep Training Computers Busy DGX-1 13K Images/Sec for each DGX-1 Assume 115KB on average for images FLASHBLADE Delivers 15 GB/s to keep all 10 DGXs in rack with training data
  19. 19. 19 DATA HUB TO SHARE DATA FREELY BUILT TO DELIVER PERFORMANCE, SIMPLICITY FOR ANY DATA PIPELINE DATA PIPELINE DYNAMIC DATA HUB “TUNED FOR EVERYTHING”Small, Random to Large, Seq. Architected for the Unknown REAL-TIME Low Latency Performance for Instant Response PARALLEL No Serial Bottlenecks for Max Throughput CLOUD-LIKE AGILITY Grow Non-Disruptively by Disaggregating Compute & Storage SIMPLE Focus More on Insights, Not Infrastructure
  20. 20. 20 © 2018 PURE STORAGE INC. PURE PROPRIETARY In our HDFS system, our cluster typically runs at 10-30% utilization of compute capacity, but at 80-85% of storage capacity… trying to increase storage capacity built out around HDFS would have been impractical. We’ve been able to take some workloads that we couldn’t run on our existing hardware, move them to FlashBlade and run them with no problem. While that’s huge for our team, it’s even more important to the lives we might impact in the future. 3X FASTER SPARK FOR GENOMICS Frank Austin Nothaft, UC Berkeley RISELab “ ”
  21. 21. 21 © 2018 PURE STORAGE INC. PURE PROPRIETARY THE ALL-FLASH DATA HUB FOR MODERN ANALYTICS 10+ PBs / RACK DENSITY FILE & OBJECT CONVERGED 1500 GB/S BW 10M+ NFS OPS BIG + FAST JUST ADD A BLADE! SIMPLE ELASTIC SCALE

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