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2020 Opening Day
Tech Talk
2020 MLB Opening Day
Tech Talk
Moneyball
Hitting real-time apps out of the
park with Big Memory
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
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.
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
2020 Opening Day
Tech Talk
Big Memory
Timothy Prickett Morgan
The Next Platform
2020 MLB Opening Day
Tech Talk
2020 Opening Day
Tech Talk
Big Memory
6
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
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
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
2020 OpeningDay
Tech Talk
Optane Persistent Memory
Mark DeMarseilles
Intel
2020 MLB Opening Day
Tech Talk
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
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
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
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
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
2020 Opening Day
Tech Talk
16
Supported on future
Intel® Xeon® Scalable Processors
Platinum and Gold SKUs
intel.com/optanedcpersist
entmemory
Rob Davis – VP Storage Technology, Nvidia Networking
BIG MEMORY MLB
OPENING DAY TECH TALK
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
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
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
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
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
FASTER PROTOCOLS SOLVES THE OTHER HALF OF THE BIG
MEMORY NETWORK PROBLEM
Big Memory
24
FASTER PROTOCOLS SOLVES THE OTHER HALF OF THE BIG
MEMORY NETWORK PROBLEM
Squeeze Play
Big Memory
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
WHAT IS RDMA?
adapter based transport
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
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
ZERO TOUCH ROCE MEANS NO SWITCH CHANGES NEEDED
ConnectX-5, All-to-all, 8 nodes, provides results similar to lossless
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
NETWORKING BIG MEMORY FUTURE PERFORMANCE
NDR
It’s a HOME RUN!
2020 Opening Day
Tech Talk
Big Memory Software
& Use Cases
Charles Fan
MemVerge
2020 MLB Opening Day
Tech Talk
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™
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
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
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
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
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)
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
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
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!
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
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
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
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
MemVerge Vision for Big Memory Industry
Compute
Memory
Performance Storage
Capacity Storage
Compute
Big Memory
Capacity Storage
2020 Opening Day
Tech Talk
Q&A
2020 MLB Opening Day
Tech Talk
2020 Opening Day
Tech Talk
Thank-you
Try it!
Contact Andrew.Degnan@memverge.com to sign-up for a PoC
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/
2020 Opening Day
Tech Talk
Raffle
50
2020 Opening Day
Tech Talk
2020 MLB Opening Day
Tech Talk

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

  • 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. 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. 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. 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. 2020 Opening Day Tech Talk Big Memory Timothy Prickett Morgan The Next Platform 2020 MLB Opening Day Tech Talk
  • 6. 2020 Opening Day Tech Talk Big Memory 6
  • 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. 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. 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. 2020 OpeningDay Tech Talk Optane Persistent Memory Mark DeMarseilles Intel 2020 MLB Opening Day Tech Talk
  • 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. 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. 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. 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. 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. 2020 Opening Day Tech Talk 16 Supported on future Intel® Xeon® Scalable Processors Platinum and Gold SKUs intel.com/optanedcpersist entmemory
  • 17. Rob Davis – VP Storage Technology, Nvidia Networking BIG MEMORY MLB OPENING DAY TECH TALK
  • 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 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 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 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 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 FASTER PROTOCOLS SOLVES THE OTHER HALF OF THE BIG MEMORY NETWORK PROBLEM Big Memory
  • 24. 24 FASTER PROTOCOLS SOLVES THE OTHER HALF OF THE BIG MEMORY NETWORK PROBLEM Squeeze Play Big Memory
  • 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 WHAT IS RDMA? adapter based transport
  • 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. 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 ZERO TOUCH ROCE MEANS NO SWITCH CHANGES NEEDED ConnectX-5, All-to-all, 8 nodes, provides results similar to lossless
  • 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 NETWORKING BIG MEMORY FUTURE PERFORMANCE NDR It’s a HOME RUN!
  • 32. 2020 Opening Day Tech Talk Big Memory Software & Use Cases Charles Fan MemVerge 2020 MLB Opening Day Tech Talk
  • 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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 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. MemVerge Vision for Big Memory Industry Compute Memory Performance Storage Capacity Storage Compute Big Memory Capacity Storage
  • 47. 2020 Opening Day Tech Talk Q&A 2020 MLB Opening Day Tech Talk
  • 48. 2020 Opening Day Tech Talk Thank-you Try it! Contact Andrew.Degnan@memverge.com to sign-up for a PoC
  • 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. 2020 Opening Day Tech Talk Raffle 50
  • 51. 2020 Opening Day Tech Talk 2020 MLB Opening Day Tech Talk