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Tech Talk: Moneyball - Hitting real-time apps out of the park with Big Memory

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A webinar hosted by MemVerge, Intel, NVIDIA, and The Next Platform. Timothy Prickett Morgan, co-editor of The Next Platform, provides his view of the Big Memory category. Mark DeMarseilles of Intel gives an update covering new Optane Persistent Memory Series 200. Rob Davis of NVIDIA explains why Big Memory needs low latency networks to distribute messages, to replicate data, and for high-availability, all without jitter. The Charles Fan of MemVerge describes Memory Machine software and different use cases including faster crash recovery, higher VM density, and high-frequency trading.

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Tech Talk: Moneyball - Hitting real-time apps out of the park with Big Memory

  1. 1. 2020 Opening Day Tech Talk 2020 MLB Opening Day Tech Talk Moneyball Hitting real-time apps out of the park with Big Memory
  2. 2. 2020 Opening Day Tech Talk Official Batting Order Joe Barnes Director MemVerge Mark DeMarseilles Technical Sales Intel Charles Fan CEO MemVerge Rob Davis VP Mellanox Timothy Pricket Morgan Co-Editor The Next Platform Manager Leading off with tech author PoV Swinging for the fence with new Optane 200 Batting clean-up with Big Memory software & 3 use cases Base stealer with low-latency networking for Big Memory
  3. 3. 2020 Opening Day Tech Talk Have Some Fun on Opening Day What happens in memory stays in memory Attend the entire Tech Talk and you get a MemVerge “What happens in memory stays in memory” t-shirt. Every attendee is automatically registered for the raffle. If you stay for the entire Tech Talk you might win an MLB jersey of your choice. Fill out your score, batting and pitching predictions in our opening day poll. The person or people that best match the actual opening results win an MLB jersey of their choice.
  4. 4. 2020 Opening Day Tech Talk https://bit.ly/openingdaytechtalk ❑ The starting pitcher on the winning team will pitch this many innings: ❑ The combined total number of runs scored by both teams will be: ❑ This many home runs will be hit during the game: ❑ There will be this many double-plays executed during the game: ❑ The combined number of hits by both teams will be: Opening Day Predictions Most right answers wins an MLB jersey of your choice choice
  5. 5. 2020 Opening Day Tech Talk Big Memory Timothy Prickett Morgan The Next Platform 2020 MLB Opening Day Tech Talk
  6. 6. 2020 Opening Day Tech Talk Big Memory 6
  7. 7. 2020 Opening Day Tech Talk Driven by the Growth of Real-Time Data IDC: Digital Transformation Driving New “Big Memory” Requirements 0% 5% 10% 15% 20% 25% 30% 0 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000 30,000,000 35,000,000 40,000,000 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 Shareofreal-timedata(%) Real-timedata(PB) Worldwide Real-Time Data and Share, 2015-2024 Real-time data (PB) Share of real-time data with Global Datashphere (%) • In 2024 there will be 143 zettabytes of data created. Worldwide, data is growing at a 26.0% CAGR • In 2024, share of real-time data grows to almost 25% • By 2021, 60-70% of the Global 2000 will have at least one mission-critical real-time workload
  8. 8. 2020 Opening Day Tech Talk Persistent Memory Revenue on the Rise $0.00 $500.00 $1,000.00 $1,500.00 $2,000.00 $2,500.00 $3,000.00 Revneue ($M) 2019 2020 2021 2022 2023 REVENUE($M) $2609M 248% CAGR 2019-2023 $65M IDC: Digital Transformation Driving New “Big Memory” Requirements
  9. 9. 2020 Opening Day Tech Talk Long Term: PMEM = DRAM Shipments Emerging Memories Find Their Direction: Objective Analysis and Coughlin Associates Emerging memories are well on their way to reach $36 billion of combined revenues by 2030. 3D XPoint memory’s sub- DRAM prices are expected to drive revenues to over $25 billion by 2030 PMEM DRAM
  10. 10. 2020 OpeningDay Tech Talk Optane Persistent Memory Mark DeMarseilles Intel 2020 MLB Opening Day Tech Talk
  11. 11. 2020 Opening Day Tech Talk Storage Memory Persistent MemoryImproving memory capacity DRAM HOT TIER HDD / TAPE COLD TIER SSD WARM TIER Delivering efficient storage Intel® 3D Nand SSD Improving SSD performance 1 Basedon Intelinternalestimates Re-architecting the memory/storage hierarchy 11 1 Basedon Intelinternalestimates Bottlenecks to MEMORY CONSTRAINED WORKLOADS demands new Memory tier
  12. 12. 2020 Opening Day Tech Talk Introducing Intel® Optane™ Persistent Memory 200 Series 12 1.MT/S is Million Transfers / Second. For Cedar Island, 2933 2DPC & 3200 1DPC is POR. Stretch target is 3200 2DPC *Many applications w illbenefit fromhigher memory frequency and bandwidth, those w ith burstyworkloads can see an additional 20%-30% bandw idth increase using Intel Bandw idth boost, Applications w hose OEMS implement eADR can see further application performance improvement Intel® Optane™ persistent memory 200 Series Up TO 3200 MT/S DDR4 12-15 wattsThermal Design Power Up to 38% Bandwidth *Improv ement vs Intel ®Optane ™ persistent memory 100 series Enhanced performance features (Improved APP Performance) Faster Higher Memory Frequency) More energy efficien (Optimized Thermals) 128GB 256GB 512GB Modules DDR4 Slots
  13. 13. 2020 Opening Day Tech Talk © COPYRIGHT 2019. INTEL CORPORATION. →Customer Pain Points SAVE MORE HELP IMPROVE TCO DRAM-ONLY ALTERNATIVE DO MORE CONSOLIDATE WORKLOADS INCREASE MEMORY SIZE GO FASTER ADD HIGH SPEED STORAGE BREAK THE IO BOTTLENECKS USE INTEL ® OPTANE Persistent MEMORY TO… Storageis too slow Workload performance Scale up is expensive DDR4 is too expensive Operational inefficiencies Not enough capacity Providing value on multiple vectors 13 128 GB DDR4 comparedto 128 GB DCPMM 45% lower 256GB DDR4 comparedto 256GB DCPMM 61% lower 152 VMs 190 VMS 25% more 768GB DDR4 192GB DDR4 1TB DCPMM 33% More 18% Lower Cost DCPMM 180-340 nano sec 8GB/S NAND 100 microsec 2GB/S
  14. 14. 2020 Opening Day Tech Talk Multiple Operating Modes To Best Fit your Needs 14 MEMORY MODE PLATFORM/OS/APP ACCESS TO High SPEED, HIGH CAPACITY MEMORY High capacity Targeting >1.2X More VMs1 Affordablecapacity 128GB, 256GB and 512GB modules Ease of adoption No code changes required 1Performance results are based on testing as of dates show n in configuration and may not reflect all publicly available security updates. See configuration disclosure for details. No product or component can be absolutely secure. For more complete information about performance and benchmark results, visit w ww.intel.com/benchmarks. “APP DIRECT” MODE SW enabled dIRECT ACCESS TO data stored persistently Persistenceprovides high availability/ less downtime Significantly faster storage Application Optimized Direct access to higher data capacity
  15. 15. 2020 Opening Day Tech Talk Operating Systems Databa ses Infrastructure & Storage AI / Analytics Software Ecosystem for Intel® Optane™ Persistent Memory 2 *Softw are support may vary per platform
  16. 16. 2020 Opening Day Tech Talk 16 Supported on future Intel® Xeon® Scalable Processors Platinum and Gold SKUs intel.com/optanedcpersist entmemory
  17. 17. Rob Davis – VP Storage Technology, Nvidia Networking BIG MEMORY MLB OPENING DAY TECH TALK
  18. 18. 18 BIG MEMORY NEEDS TO BE ABLE TO SCALE Otherwise Its Amazing Performance is Limited to Small Applications ▪Scale-out ▪Capacity expansion focused on adding new hardware instead of increasing existing hardware capacity ▪MemVerge application provides sharing functions Deep Bench Cluster of shared Big Memory
  19. 19. 19 BIG MEMORY NEEDS TO BE TIERABLE Otherwise Its Amazing Performance is Limited to Smaller Data Sets ▪Tiering ▪Efficiently using memory and storage technologies according to importance or use frequency of the data ▪MemVerge software provides Tiering functions Nolan Ryan FastBig Memory Performance
  20. 20. 20 BIG MEMORY NEEDS HIGH AVAILABILITY Otherwise Its Persistence is Not Usable in the Enterprise ▪High Availability (HA) ▪Storage system that is continuously operational or has very little downtime ▪Redundancy is a key feature of HA Big Memory ▪Allows data to be kept in more than one place and eliminates a single points of failure ▪MemVerge software provides HA function Backup Pitcher Big Mem.
  21. 21. 21 CORE REQUIREMENTS FOR NETWORKING BIG MEMORY ▪Big Memory is really fast ▪Needs ultra low-latency network ▪Needs ultra high bandwidth network ▪Needs predictability, even under load ▪Needs Fairness (QOS) ▪Needs Very Low Packet Loss Base Stealing Speed Big Memory (PM)
  22. 22. 22 FASTER NETWORK HARDWARE SOLVES HALF OF THE BIG MEMORY NETWORK PROBLEM… Ethernet & InfiniBand End-to-End 25, 40, 50, 56, 100, 200Gb Going to 400Gb next year
  23. 23. 23 FASTER PROTOCOLS SOLVES THE OTHER HALF OF THE BIG MEMORY NETWORK PROBLEM Big Memory
  24. 24. 24 FASTER PROTOCOLS SOLVES THE OTHER HALF OF THE BIG MEMORY NETWORK PROBLEM Squeeze Play Big Memory
  25. 25. 25 FASTER RDMA PROTOCOL SOLVES THE OTHER HALF OF THE BIG MEMORY NETWORK PROBLEM 100-400Gb RDM A Big Memory Big Memory Big Mem
  26. 26. 26 WHAT IS RDMA? adapter based transport
  27. 27. 27NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. RDMA NOW COMMON ACROSS ALL STORAGE TYPES Big Memory (PM) RPM Block File Object RDMA SMB (CIFS) NFS Ceph iSERSMB Direct Ceph over RDMA NVMe- oF/RDMA Swift ▪ RDMA for optimal performance • InfiniBand & RoCE o NVMe-oF o Nvidia GPU Direct Storage ▪ Persistent Big Memory (3D-XPoint) S3 FC iSCSI NFSoRDMANFSoRDMA NVMe- oF/TCP
  28. 28. 4 Reasons Why Big Memory Needs RDMA 1. Pub/Sub Distributing messages to many servers with low-latency and jitter 3. HA Replicating memory to other servers for failover 4. Scale-Out Create memory lakes by pooling server memory RDMA RDMA 2. App Migration Memory Machine migrates app + memory to other servers RDMA RDMA
  29. 29. 29 ZERO TOUCH ROCE MEANS NO SWITCH CHANGES NEEDED ConnectX-5, All-to-all, 8 nodes, provides results similar to lossless
  30. 30. 30 IMPORTANCE OF NETWORK LATENCY WHEN NETWORKING BIG MEMORY Logarithmicscale Nvidia Ethernet Switch & Adapter Network hops multiply latency Request/Response Big Mem. 200Gb 100Gb Run Down InfiniBand900ns 1.3μs Common Ethernet Switch & Adapter
  31. 31. 31 NETWORKING BIG MEMORY FUTURE PERFORMANCE NDR It’s a HOME RUN!
  32. 32. 2020 Opening Day Tech Talk Big Memory Software & Use Cases Charles Fan MemVerge 2020 MLB Opening Day Tech Talk
  33. 33. 33 A software-defined memory service that virtualizes DRAM and Persistent Memory • Compatible with DRAM, no application rewrite necessary • Larger capacity, Similar Performance and Lower Cost than DRAM Featuring Data Services designed for memory • World’s first ZeroIO™ in-memory snapshot • Fast crash recovery to any snapshot • Clone new application instance from any snapshot without replicating memory MemVerge Memory Machine™
  34. 34. 2020 Opening Day Tech Talk Uses Cases: Real-Time Applications AI/ML inference like fraud detection,image classificationand recommendationengines Latency-sensitive transactional workloads such as trading applications in capital markets According to IDC, by 2021, 60-70% of the Global 2000 organizations will have at least one mission-critical real-time workloads like these. Memory-intensive applications in media & entertainment, healthcare, and oil & gas
  35. 35. 2020 Opening Day Tech Talk The Need • Limit disruption to business when an in-memory app crashes The Problem • It takes a long time for an in- memory app to restart after crash or planned shutdown Memory Machine Use Case Crash Recovery
  36. 36. 2020 Opening Day Tech Talk MemVergeSolution • AutoSave: Memory Machine takes instant ZeroIO™ snapshots as frequently as every 1 minute • Application is automatically restarted from the last snapshot after crash, and it is FAST! Memory Machine Use Case Crash Recovery 1TB
  37. 37. 2020 Opening Day Tech Talk kdb+ Snapshot and Restore Performance 37 Seconds 1.2 2.11 1 144 (2.4 min) 510 (8.5 min) 0 100 200 300 400 500 600 220 GB 380 GB Snapshot (Memory Machine) Restore from Snapshot (Memory Machine) Restore from Log (Baseline) Snapshot Restore Snapshot Restore
  38. 38. 2020 Opening Day Tech Talk kdb+ Performance Stress Test - Insertion 38 2.3 25 111 200 54 70 72 65 2.0 12 53 125 45 56 62 62 2.2 20 125 250 95 117 127 130 0 50 100 150 200 250 300 Single insert Bulk insert 10 Bulk insert 100 Bulk insert 1000 Bulk insert 10000 Bulk insert 15000 Bulk insert 20000 Bulk insert 25000 Insertion Performance (Million Inserts per Second) DRAM (Baseline) PMEM (MemVerge) 1G DRAM + PMEM (MemVerge)
  39. 39. 2020 Opening Day Tech Talk The Need • To create additional instances of In-Memory Databases for other applications, DevOps, QA, etc. Memory Machine Use Case Cloning • Multipleinstances of physical memory are expensive • Cloning databases is time-consuming The Problem
  40. 40. 2020 Opening Day Tech Talk The MemVerge Solution • ZeroIO™ snapshots to memory as frequent as every minute • A new in-memory database instance can be created from any past snapshot without a physical memory copy Memory Snapshot + Clone Replay Restart Memory Machine Use Case Cloning
  41. 41. 2020 Opening Day Tech Talk Cloning a Redis Database with 300M Keys 41 900,240 (15 min) 581 (0.5 sec) 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 900,000 1,000,000 DRAM PMEM (Memory Machine) Milliseconds 1,500X Faster No duplication of memory resources!
  42. 42. 2020 Opening Day Tech Talk The Need • Optimize server utilization by increasing VM density & decreasing cost per VM The Problem • Memory capacity is the bottleneck Memory Machine Use Case KVM
  43. 43. 2020 Opening Day Tech Talk The MemVerge Solution • Memory Machine™ software multiplies the amount of memory available to the hypervisor • Adjustable DRAM:PMEM ratio enables memory performance similar to DRAM Memory Machine Use Case KVM DRAM PMEM Memory Machine
  44. 44. 2020 Opening Day Tech Talk MySQL performance 44 0 20000 40000 60000 80000 100000 120000 140000 160000 10G Data 40G Data SysbenchQPS DRAM PMEM Cache-2G Cache-4G Cache-8G Cache-16G
  45. 45. 45 Memory Machine™ Enterprise-Class Memory Virtualization Software Key Benefits to Real-TimeApps Scalability Terabytes of DRAM-speed memory available to memory-intensive apps Availability ZeroIO™ Snapshot enables faster crash recovery Agility Instant Clones without duplicating of physical memory Compatibility No changes to application necessary
  46. 46. MemVerge Vision for Big Memory Industry Compute Memory Performance Storage Capacity Storage Compute Big Memory Capacity Storage
  47. 47. 2020 Opening Day Tech Talk Q&A 2020 MLB Opening Day Tech Talk
  48. 48. 2020 Opening Day Tech Talk Thank-you Try it! Contact Andrew.Degnan@memverge.com to sign-up for a PoC
  49. 49. 2020 Opening Day Tech Talk Learn More About Big Memory 49 Persistent Memory Breakthrough Memory Optimized for Data-Centric Workloads https://www.intel.com/content/www/us/en/architecture-and-technolog y/optane- dc-persistent-memor y.html Intel® Optane™ PersistentMemory Workload Solutions https://www.intel.com/content/www/us/en/architecture-and-technolog y/optane- persistent-memor y-soluti ons.html Gartner's Donald Feinberg on PersistentMemoryTechnology https://youtu.be/9oQ78M51RfQ RDMA Networks Improve Data Transfer Efficiency Through RDMA https://www.mellanox.com/products/adapter-ethernet-SW/RDMA-RoCE-Ether net-Network-Efficiency Learn how RDMA Accelerates Access to Data https://www.mellanox.com/sites/default/files/related- docs/technical-briefs/TB_RDMA.pdf Video – RDMA over Converged Ethernet (RoCE) https://youtu.be/mu2v95feops Big Memory Software MemVerge Corporate Brochure https://www.memverge.com/web/wp-content/uploads/2020/07/C orporate-Brochure_2020.pdf Memory Machine Software Data Sheet https://www.memverge.com/web/wp-content/uploads/2020/06/Data-Sheet_M emory-Machine.pdf IDC Big Memory Definition and PMEM Forecast https://www.slideshare.net/MemVerge/ The Next Platform Coverage Those Without PersistentMemoryare Fated to Repeatit https://www.nextplatfor m.com/2019/05/20/those- without- persistent-memor y-are-fated-to-repeat-it/ Getting Around The Limits ofMemory to Accelerate Applications https://www.nextplatfor m.com/2019/08/18/getting-around-the-limits- of-memory-to-accelerate-applications/
  50. 50. 2020 Opening Day Tech Talk Raffle 50
  51. 51. 2020 Opening Day Tech Talk 2020 MLB Opening Day Tech Talk

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