GPU Instances on Amazon EC2
John Phillips, Sr. Product Manager, Amazon EC2
November 15, 2013

© 2013 Amazon.com, Inc. and ...
Agenda
Overview of GPU Instances
Gyuri Ordody with Autodesk: Evolution of CAD on AWS
Teng Lin with Schrodinger: Drug Disco...
Instance Types Today
G2 Instances
new
existing

m1.small

m1.xlarge
m1.large
m1.small

2006

2007

Entry into GPU
space

c...
Why GPUs? Parallel Performance
Example CPU

Example GPU
Coprocessor

Processing cores

8

2,688

Clock frequency

2.6GHz

...
cg1.4xlarge
2 x NVIDIA GF104 GPU (Fermi / Tesla)
Intel Xeon X5570
16 vCPUs, 22.5 GiB of RAM
2 x 840 GB storage
10 Gbps NIC
Customer Feedback
g2.2xlarge
1 NVIDIA GK104 GPU (Kepler / GRID)

2.6 GHz Sandy Bridge CPU w/ Turbo enabled
8 vCPUs, 15 GiB of RAM

60GB SSD ...
$0.65 per hour
Why remote graphics in Amazon EC2?
Accessibility
Quality of service
Business agility
Collaboration
Data security
And…
AWS Under Your Desk
GPU Instances on AWS:
Desktop Apps Are The New Web Apps
Gyuri Ordody, Autodesk
November 15, 2013

© 2013 Amazon.com, Inc. ...
About Autodesk
Autodesk started more than 30 years ago,
with 16 employees and one software title.

12
About Autodesk
Today: an industry leader in design software for the building, manufacturing,
infrastructure and entertainm...
Architecture, Engineering and Construction

Image courtesy of Castro Mello Architects

Image courtesy of Castro Mello Arch...
Digital Prototyping

Image courtesy of Brimrock Group Inc. and Mechanix Design Solutions Inc.

15
Media & Entertainment

16
CAD Evolution

IBM PC 5150 with keyboard and green monochrome monitor (5151), running MS-DOS 5.0 © Boffy
b

17
CAD Evolution

Lines, Arcs, Circles

Features, Shapes, Blocs

Intelligent Objects

18
Huge Datasets

Image courtesy of Hunt Construction Group and SHoP

19
Simulation, Analysis

20
21
Design = Visualization
• High-end desktop
workstation
–
–
–
–

CPU (Xeon multicore)
RAM (16GB)
GPU (DirectX 9-11)
Fast Dis...
Design = Collaboration

23
Design = Collaboration

+

24
Design = Collaboration

+

Design Graph

25
Strategies
• Create new cloud services on server clusters
– Write or rewrite from scratch

• Move desktop technology to he...
27
Collaboration – Using the AWS Cloud
•
•
•
•
•

Access it anywhere
Access using any device
Seamless collaboration
Editing f...
Application Remoting
Overview
Home / Office

Desktop Apps

Internet

Keyboard,
mouse, USB

Player
Bitmap / Video

EC2 Inst...
Application Remoting
Overview
Home / Office

Desktop Apps

Internet

Keyboard,
mouse, USB

Player
Bitmap / Video

EC2 Inst...
Application Remoting
Overview
Home / Office

Desktop Apps

Internet

Keyboard,
mouse, USB

Player
Bitmap / Video

EC2 Inst...
Autodesk Online Application - Architecture
Internet

Controller
EC2 Instance

…

Client
Region 1

User

Controller
EC2 Ins...
Autodesk Online Application - Architecture
Internet

Controller
EC2 Instance
Client

App Servers

Application Settings

Us...
Application Remoting – Instance sharing
Home / Office 1

Autodesk Desktop Apps

Internet

…
Home / Office n

EC2 Instance
...
Desktop Applications – Data Exchange
N GB/exchange

Data Sets

35
Cloud data exchange – Predictable Data Traffic
Data references
N kb/exchange

Data references
N kb/exchange

36
Cloud data exchange – Predictable Data Traffic
Data references
N kb/exchange
Data
references +
Video Stream
1 GB/hr

37
A360 and the AWS Cloud
Identity

EC2 + RDS

Storage

S3 DynamoDB

Supporting
Infrastructure

Analysis

EC2

EMR

RDS

Simu...
Application + Cloud Integration
Internet

Autodesk
Desktop Apps

Autodesk
Identity
Service

Ec2 + RDB

Autodesk
Storage
Se...
Application + Cloud Integration
Internet

Autodesk
Desktop Apps

Autodesk
App
Player

Autodesk
Desktop
Apps

Identity

EC2...
Application + Cloud Integration
Internet

Autodesk
App Player

Autodesk
Desktop
Apps

Identity

EC2 + RDB
GPU!
Storage

Us...
Autodesk Apps in the Cloud
Without Amazon EC2 - GPU Instances

42
Autodesk Apps in the Cloud
With Amazon EC2 - GPU Instances

43
Application + Cloud Integration
Internet

Autodesk
App Player

Autodesk
Desktop
Apps

Identity

EC2 + RDB
GPU!
Storage

Us...
Application + Cloud Integration
Internet

Autodesk
Desktop
Apps

Identity

*

EC2 + RDB
GPU!
Storage

User
Client

S3 +
DB...
Application + Cloud Integration
Internet
Identity

Autodesk
Desktop
Apps

Supporting
Infrastructure

Storage

Translation
...
Demo: Running Design Apps
In a Browser

Demos
• Live
• YouTube: http://www.youtube.com/watch?v=lU85EjvTyz0

47
Drug Discovery on AWS
Teng Lin, Senior Principal Scientist, Schrödinger
November 15, 2013

© 2013 Amazon.com, Inc. and its...
Drug discovery and development stages
• It takes $800 Million to $1 Billion and 10 to 15
years to develop a blockbuster

h...
Simple facts about drug discovery
• Each development candidate has a value of
$50-100M
• But the overhead of producing the...
Schrödinger
• Providing software solutions and services for life
sciences and materials research
Ligand-protein binding
• Altering receptor protein conformation, and
consequently changing biological functions.
• Binding...
Free Energy Perturbation (FEP)
• Schrödinger’s FEP product
– Can predict binding affinity very accurately

• Key features
...
GPU is significantly faster
• Each edge takes 3 or more days on 96 cores
– Slow and unreliable due to cross node communica...
How can FEP help drug discovery?
• Traditional drug design
– Takes weeks or even months to synthesize a compound
– Costs $...
Why AWS?
• Scalability
– Performed virtual screening using 50,000-core on AWS

• Security
• Price per FEP job
– It takes u...
FEP on cloud
• Next version will be cloud oriented
• Data will be processed and visualized on cloud
Auto Scaling
Mobile Cl...
Retrospective Study
Binding Affinity Prediction (kcal/mol)

-4
-5

-6
-7
-8
-9
-10
-11
-12

y = 1.07x + 0.652; R² = 0.599
...
Blind test with company X on AWS
• 9 out of top 10 are active compounds
– Probability of achieving result this good is <1%...
Blind test with company Y on AWS
• 8 out of top 10 are the most active compounds
– Probability of achieving result this go...
Prospective FEP with Company Z on AWS
• 1/3 of molecules are active instead of 1/7
• Company Z uses FEP on many projects
2...
Summary
• Computer aid drug design plays a critical role in
drug discovery
• Combining with GPU computing, accurate
modeli...
Please give us your feedback on this
presentation

CPN210
As a thank you, we will select prize
winners daily for completed...
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Getting Cloudy with Remote Graphics and GPU Compute Using G2 instances (CPN210) | AWS re:Invent 2013

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Amazon EC2 now offers a new GPU instance capable of running graphics and GPU compute workloads. In this session, we take a deeper look at the remote graphics capabilities of this new GPU instance, the tooling required to get started, and a live demo of applications streamed from our West Coast regions. We also explore the benefits of hosting your 3D graphics applications in the AWS cloud, where you can harness the vast compute and storage resources.

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Transcript of "Getting Cloudy with Remote Graphics and GPU Compute Using G2 instances (CPN210) | AWS re:Invent 2013"

  1. 1. GPU Instances on Amazon EC2 John Phillips, Sr. Product Manager, Amazon EC2 November 15, 2013 © 2013 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.
  2. 2. Agenda Overview of GPU Instances Gyuri Ordody with Autodesk: Evolution of CAD on AWS Teng Lin with Schrodinger: Drug Discovery on AWS Questions from audience (if there’s time)
  3. 3. Instance Types Today G2 Instances new existing m1.small m1.xlarge m1.large m1.small 2006 2007 Entry into GPU space c1.medium c1.xlarge m1.xlarge m1.large m1.small m2.2xlarge m2.4xlarge c1.medium c1.xlarge m1.xlarge m1.large m1.small cc1.4xlarge cg1.4xlarge t1.micro m2.xlarge m2.2xlarge m2.4xlarge c1.medium c1.xlarge m1.xlarge m1.large m1.small cc2.8xlarge cc1.4xlarge cg1.4xlarge t1.micro m2.xlarge m2.2xlarge m2.4xlarge c1.medium c1.xlarge m1.xlarge m1.large m1.small hs1.8xlarge m3.xlarge m3.2xlarge hi1.4xlarge m1.medium cc2.8xlarge cc1.4xlarge cg1.4xlarge t1.micro m2.xlarge m2.2xlarge m2.4xlarge c1.medium c1.xlarge m1.xlarge m1.large m1.small 2008 2009 2010 2011 2012 c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge i2.large i2.xlarge i2.2xlarge i2.4xlarge i2.8xlarge g2.2xlarge cr1.8xlarge hs1.8xlarge m3.xlarge m3.2xlarge hi1.4xlarge m1.medium cc2.8xlarge cc1.4xlarge cg1.4xlarge t1.micro m2.xlarge m2.2xlarge m2.4xlarge c1.medium c1.xlarge m1.xlarge m1.large m1.small 2013
  4. 4. Why GPUs? Parallel Performance Example CPU Example GPU Coprocessor Processing cores 8 2,688 Clock frequency 2.6GHz 732MHz Memory bandwidth 51.2 GB/s / socket 250GB/s (DDR5) Peak Gflops (single) 333* 3,950** Product Peak Gflops (double) Total Memory 166* 1,310*** >>4GB 6GB * 256-bit AVX addition + 256 AVX multiplication /cycle/core ** 32-bit FMA /cycle/core *** 64-bit FMA /cycle/2core
  5. 5. cg1.4xlarge 2 x NVIDIA GF104 GPU (Fermi / Tesla) Intel Xeon X5570 16 vCPUs, 22.5 GiB of RAM 2 x 840 GB storage 10 Gbps NIC
  6. 6. Customer Feedback
  7. 7. g2.2xlarge 1 NVIDIA GK104 GPU (Kepler / GRID) 2.6 GHz Sandy Bridge CPU w/ Turbo enabled 8 vCPUs, 15 GiB of RAM 60GB SSD storage EBS-Optimized up to 1Gbps Frame Capture and Encoding APIs
  8. 8. $0.65 per hour
  9. 9. Why remote graphics in Amazon EC2? Accessibility Quality of service Business agility Collaboration Data security And…
  10. 10. AWS Under Your Desk
  11. 11. GPU Instances on AWS: Desktop Apps Are The New Web Apps Gyuri Ordody, Autodesk November 15, 2013 © 2013 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.
  12. 12. About Autodesk Autodesk started more than 30 years ago, with 16 employees and one software title. 12
  13. 13. About Autodesk Today: an industry leader in design software for the building, manufacturing, infrastructure and entertainment industries 13
  14. 14. Architecture, Engineering and Construction Image courtesy of Castro Mello Architects Image courtesy of Castro Mello Architects 14
  15. 15. Digital Prototyping Image courtesy of Brimrock Group Inc. and Mechanix Design Solutions Inc. 15
  16. 16. Media & Entertainment 16
  17. 17. CAD Evolution IBM PC 5150 with keyboard and green monochrome monitor (5151), running MS-DOS 5.0 © Boffy b 17
  18. 18. CAD Evolution Lines, Arcs, Circles Features, Shapes, Blocs Intelligent Objects 18
  19. 19. Huge Datasets Image courtesy of Hunt Construction Group and SHoP 19
  20. 20. Simulation, Analysis 20
  21. 21. 21
  22. 22. Design = Visualization • High-end desktop workstation – – – – CPU (Xeon multicore) RAM (16GB) GPU (DirectX 9-11) Fast Disk 22
  23. 23. Design = Collaboration 23
  24. 24. Design = Collaboration + 24
  25. 25. Design = Collaboration + Design Graph 25
  26. 26. Strategies • Create new cloud services on server clusters – Write or rewrite from scratch • Move desktop technology to headless server technology – EC2 instances and Amazon S3 as backend – Recreate UI functionality in the browser • Deploy existing desktop apps in the cloud – Reuse engine and GUI 26
  27. 27. 27
  28. 28. Collaboration – Using the AWS Cloud • • • • • Access it anywhere Access using any device Seamless collaboration Editing from anywhere Data close to application 28
  29. 29. Application Remoting Overview Home / Office Desktop Apps Internet Keyboard, mouse, USB Player Bitmap / Video EC2 Instance 29
  30. 30. Application Remoting Overview Home / Office Desktop Apps Internet Keyboard, mouse, USB Player Bitmap / Video EC2 Instance 30
  31. 31. Application Remoting Overview Home / Office Desktop Apps Internet Keyboard, mouse, USB Player Bitmap / Video EC2 Instance 31
  32. 32. Autodesk Online Application - Architecture Internet Controller EC2 Instance … Client Region 1 User Controller EC2 Instance Region N Controller EC2 Instance Region 2 32
  33. 33. Autodesk Online Application - Architecture Internet Controller EC2 Instance Client App Servers Application Settings User Data EC2 Instances Default User Data Session Data Connection S3 SimpleDB User Custom Scaling App Server AMI Region 33
  34. 34. Application Remoting – Instance sharing Home / Office 1 Autodesk Desktop Apps Internet … Home / Office n EC2 Instance Internet 34
  35. 35. Desktop Applications – Data Exchange N GB/exchange Data Sets 35
  36. 36. Cloud data exchange – Predictable Data Traffic Data references N kb/exchange Data references N kb/exchange 36
  37. 37. Cloud data exchange – Predictable Data Traffic Data references N kb/exchange Data references + Video Stream 1 GB/hr 37
  38. 38. A360 and the AWS Cloud Identity EC2 + RDS Storage S3 DynamoDB Supporting Infrastructure Analysis EC2 EMR RDS Simulation EC2 EMR 38
  39. 39. Application + Cloud Integration Internet Autodesk Desktop Apps Autodesk Identity Service Ec2 + RDB Autodesk Storage Service User Client S3 + DB AWS Cloud 39
  40. 40. Application + Cloud Integration Internet Autodesk Desktop Apps Autodesk App Player Autodesk Desktop Apps Identity EC2 + RDB No GPU Storage User Client S3 + DB EC2 AWS Cloud 40
  41. 41. Application + Cloud Integration Internet Autodesk App Player Autodesk Desktop Apps Identity EC2 + RDB GPU! Storage User Client S3 + DB EC2 AWS Cloud 41
  42. 42. Autodesk Apps in the Cloud Without Amazon EC2 - GPU Instances 42
  43. 43. Autodesk Apps in the Cloud With Amazon EC2 - GPU Instances 43
  44. 44. Application + Cloud Integration Internet Autodesk App Player Autodesk Desktop Apps Identity EC2 + RDB GPU! Storage User Client S3 + DB EC2 AWS cloud 44
  45. 45. Application + Cloud Integration Internet Autodesk Desktop Apps Identity * EC2 + RDB GPU! Storage User Client S3 + DB EC2 AWS cloud 45
  46. 46. Application + Cloud Integration Internet Identity Autodesk Desktop Apps Supporting Infrastructure Storage Translation * GPU! Search User Client Simulation EC2 Instances AWS cloud 46 Analysis
  47. 47. Demo: Running Design Apps In a Browser Demos • Live • YouTube: http://www.youtube.com/watch?v=lU85EjvTyz0 47
  48. 48. Drug Discovery on AWS Teng Lin, Senior Principal Scientist, Schrödinger November 15, 2013 © 2013 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.
  49. 49. Drug discovery and development stages • It takes $800 Million to $1 Billion and 10 to 15 years to develop a blockbuster http://www.innovation.org/drug_discovery/objects/pdf/RD_Brochure.pdf
  50. 50. Simple facts about drug discovery • Each development candidate has a value of $50-100M • But the overhead of producing these in pharmaceutical company is $35-70M – Success rate is only 1 in 3 – Thousands of molecules synthesized • Pharmaceutical Industry needs to overcome the innovation deficit in drug discovery process
  51. 51. Schrödinger • Providing software solutions and services for life sciences and materials research
  52. 52. Ligand-protein binding • Altering receptor protein conformation, and consequently changing biological functions. • Binding affinity is critical for drug discovery Yibing Shan etal Journal of the American Chemical Society, vol. 133, no. 24, 2011, pp. 9181–9183.
  53. 53. Free Energy Perturbation (FEP) • Schrödinger’s FEP product – Can predict binding affinity very accurately • Key features – – – – – – Better sampling algorithm High quality Force Field Perturbation network Automated workflow GPU support Cloud capable
  54. 54. GPU is significantly faster • Each edge takes 3 or more days on 96 cores – Slow and unreliable due to cross node communication – Perturbation network makes it even worse 120.0 109.8 Speed (ns/day) 100.0 86.4 80.0 60.8 60.0 DHFR APOA1 40.0 26.3 20.0 18.5 15.2 21.0 4.9 0.0 8 x Intel Xeon X5672 GeForce GTX780 Amazon Tesla M2050 Amazon Geforce Grid K520
  55. 55. How can FEP help drug discovery? • Traditional drug design – Takes weeks or even months to synthesize a compound – Costs $1,000 to $5,000 per compound – Synthesize thousands of compounds per project • In-silico design using FEP – Takes 72 GPU hours (~6 hours per calculation with 12 GPUs) – Costs about $75, and the price keeps going down – “want to do 1000 calculations per day”
  56. 56. Why AWS? • Scalability – Performed virtual screening using 50,000-core on AWS • Security • Price per FEP job – It takes us two months to get GTX-780 cluster up running $75.60 $80.00 $60.00 $40.00 $20.00 $16.61 $32.76 $32.01 $28.28 $17.62 $12.67 $3.78 $0.00 GTX-780 (50% Tesla K20 (70% Spot Instance 3-yr HEAVY On-demand util) util) CG1 reserved (100% Instance CG1 util) CG1 Spot Instance 3-yr HEAVY G2 reserved (100% util) G2 On-demand Instance G2
  57. 57. FEP on cloud • Next version will be cloud oriented • Data will be processed and visualized on cloud Auto Scaling Mobile Client Cluster DB InstanceScaling GPU Cluster Auto Internet Gateway Client Amazon EC2 VPN Gateway Web Servers VPN Connection VPN Connection Traditional Server Corporate Data Center
  58. 58. Retrospective Study Binding Affinity Prediction (kcal/mol) -4 -5 -6 -7 -8 -9 -10 -11 -12 y = 1.07x + 0.652; R² = 0.599 (Linear regression to all ~150 ligands across multiple systems) -13 -14 -14 -13 -12 -11 -10 -9 -8 -7 Binding Affinity (kcal/mol) -6 -5 -4
  59. 59. Blind test with company X on AWS • 9 out of top 10 are active compounds – Probability of achieving result this good is <1% – “make half as many compounds” – “save years of time on the project” • Company X signed a88 contract after the test 90 Count 80 70 60 50 40 30 20 10 0 66 59 48 19 6 Highest 3 1 Binding Affinity Lowest
  60. 60. Blind test with company Y on AWS • 8 out of top 10 are the most active compounds – Probability of achieving result this good is <1% • Company Y wants us to provide a turn key solution 20 19 18 16 Count 14 12 10 10 10 8 6 4 4 1 2 8 0 Highest 1 1 Binding Affinity Lowest
  61. 61. Prospective FEP with Company Z on AWS • 1/3 of molecules are active instead of 1/7 • Company Z uses FEP on many projects 25 23 19 Count 20 15 10 Non-FEP 10 9 FEP predict to be active FEP predict to be inactive 5 4 4 2 0 0 Highest 0 4 1 1 1 Binding Affinity 2 0 0 0 1 Lowest
  62. 62. Summary • Computer aid drug design plays a critical role in drug discovery • Combining with GPU computing, accurate modeling tools like FEP will accelerate the drug discovery process • Cloud is a viable solution for high performance computing, in terms of pricing and scalability • Amazon is the leader for GPU computing at cloud
  63. 63. Please give us your feedback on this presentation CPN210 As a thank you, we will select prize winners daily for completed surveys!
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