The document discusses how Pure Storage's FlashBlade storage system is designed to be a data hub that can power various modern data and analytics workloads including AI, machine learning, data warehousing, and streaming analytics. It provides high throughput, scale-out performance for file and object storage, and is purpose built to deliver the performance needed for these next generation workloads. FlashBlade uses a scale-out architecture with blades, networking, and software that allows for linear scaling of performance and capacity.

1. ML + AI = FB
Bogusz Błaszkiewicz

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
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. 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
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
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
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
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
ANNOUNCING
FLASHBLADE WITH 150 BLADES
UNDER SINGLE NAMESPACE
2x CAPACITY WITH SAME SIMPLICITY
DIRECTED AVAILABILITY

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
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
EVERGREEN STORAGE
ALL-INCLUSIVE
SOFTWARE
FLAT AND FAIR
MAINTENANCE
CAPACITY
CONSOLIDATION
LYS
GUARANTEE
DIFFERENTIATED BUSINESS MODEL
8TB 52TB

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
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
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. 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. © 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
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
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 © 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 © 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