HighPerformance   Cloud ComputingSupercomputing 2011
Hello
Thank you
HPC withAWS
Understand theservices, tools andpatterns forbuildinghigh performancesystems in the
AGENDA  SC11 - Monday 14th November, 2011Cloud ConceptsBuilding BlocksTechnica l & Scientific ComputingL oosely Coupled Sys...
There Will Be Code
CloudConceptsA prelude
Consumer     Seller business   business
Decades of experience Operations, management and             scale
Programmatic access
Unexpected innovation
Blinding flash of   the obvious
Five years young
Infrastructure services
Compute      Storage  Placeholder             ServicesDatabases            & Support
Idea   Results
Idea                   Results       Heavy lifting
ScaleRedundancy                     Orchestrati                                   on               70% Idea               ...
30%Idea                    Results       Infrastructure
Idea         Results       AWS
Idea         Results       AWS
Five things Iwish I’d knownwhen Iwas gettingstarted.
1: Signing up
On the web
Free tier For new customers:aws.amazon.com/free
750 hours of compute10Gb network attached storage5Gb object storage750 hours of computeKey/value store, notifications,messa...
2: Interacting
HTTP, REST, SOAP
API driven HTTP, REST, SOAP
CLI
ec2-run-instances
ec2-terminate-instances
Java, Python, Ruby, .Net, PHP,       iOS and Android
SDKJava, Python, Ruby, .Net, PHP,       iOS and Android
Management  console
Linux
Certificate-based root  access
mza$ ssh -i web/us-east/aws-web.pemroot@ec2-204-236-247-169.compute-1.amazonaws.comLast login: Wed Jun 22 11:15:20 2011 fr...
Windows
Administrator  access
3: Storage options
Ephemeral storage
Included           with         compute    Ephemeral     storage  Lost at                Not backedterminatio             ...
When it’s gone,  it’s gone
Hands-on
Elastic Block StoreHands-on
Network    Mount as attached    volumeElastic Block StoreSnapshot     Persistent
Hands-on
S3Hands-on
Highly              Highlydurable            available          S3     Tolerant to        two     simultaneo
durability
99.999999999%   durability
Objects in S3Billions of objects                                                556B      600      450      300      150  ...
370,000 peaktransactions per second
Payment options
Pay as you go
Gb/month
ECU/hour
No minimum
No subscriptions
Pricing tiers
Consolidated   billing
Options
On-demand
Reservedcapacity
Hands-on
Spot MarketHands-on
Bandwidth
Free inbound
Import/Export
Reducedoutbound
Pricing calculator
aws.amazon.com/calculator
5. Availability    Zones
us-east-1  us-west-1  us-west-2us-gov-west-1  eu-west-1ap-southeast-1ap-northeast-1
eu-west-1aeu-west-1b   eu-west-1c
BuildingblocksservicesFoundational
Compute
Elastic Compute Cloud
EC2Elastic Compute Cloud
Hands-on
Elastic compute infrastructureHands-on
ECU:Equivalent to 1.0 - 1.2 GHz 2007 Opteron               or 2007 Xeon
ECU:EC2 Compute UnitEquivalent to 1.0 - 1.2 GHz 2007 Opteron               or 2007 Xeon
Instance types
ClustMicro         er$0.02    $2.10
Standard (m1) 1 ECU. 1.7 Gb memory.   160 Gb ephemeral        storage.
High memory    (m2)Up to 26 ECU. 8 cores. 68.4 Gb           memory. 1.69 Tb ephemeral storage.
High CPU (c1)Up to 20 ECU. 8 cores. 7 Gb memory.     1.69 Tb ephemeral storage.
Higherperformance
MPI workloads
Bandwidth intensive
Hands-on
CC:Cluster ComputeHands-on
2 x Intel Xeon     557023 Gb memory 1.7 Tb disk  33.5 ECUs
HVM
10 gig E
Placement groups
Full bisectional  bandwidth
Linpack
November 2010Cores     7040 R max    41.82 R peak   82.51
November 2010  231
June 2011451
November 2011
November 2011 42
WIEN2K Parallel                                                                    Performance                            ...
GPU computation
Hands-on
CG:Cluster Compute   with gpGPUHands-on
2 x NVIDIA  M2050
2 x Intel Xeon 5570  23 Gb memory     1.7 Tb disk  2 x NVIDIA    M2050
Flexible cluster    control
API
Hands-on
SGEHands-on
LSF
Condor
Rocks+
Slurm
Included with all instances     and block storage
CloudWatchIncluded with all instances     and block storage
Custom metrics
Storage
Simple Storage Service
S3Simple Storage Service
Files in directories
Objects in buckets
http://s3.amazonaws.com/bucketname/objectid http://bucketname.s3.amazonaws.com/objectid
https://s3.amazonaws.com/bucketname/objectidhttps://bucketname.s3.amazonaws.com/objectid
5Tb
Large object  support    5Tb
Parallel uploads
Import/Export
Managedencryption
99.99% durability
Reducedredundancy  storage99.99% durability
Elastic Block Store
EBSElastic Block Store
Flexible, off-instance block    storage
1Gb to 1Tb
Scalable1Gb to 1Tb
Exposed as a device
Attached to arunning instance  Exposed as a device
Snapshot to S3
Hands-on
Public DatasetsHands-on
Databases
Databases on EC2
Oracle and MySQL
Managed. High availability.     Read replicas.
RelationalDatabase ServiceManaged. High availability.     Read replicas.
High scale. Highly available.    Key/attribute store
SimpleDBHigh scale. Highly available.    Key/attribute store
No server toprovision or  manage.
Perfect formetadata
Messaging &notifications
Hands-on
Simple Queue      ServiceHands-on
Hands-on
Simple     Notification       ServiceHands-on
Technical &ScientificComputing
Elasticity
Research is  bursty
Traditionalcapacity is   static
Capacity           Predicted capacity                  Estimated                   demand                        Time
Capacity                                  Infrastructure                                Infrastructure                   I...
Capacity                    Infrastructure            Real           demand                                Time
Capacity            Elastic           capacity                 Real                demand                         Time
Rapid response
Removingconstraints
Research isconstrained
Constrained by      static infrastructure
Unconstrained
Larger systems,more molecules,  more stars, higher order   species...
Unconstrained  by scale
30,000 cores
Unconstrained   by timeUpcoming conference, grant submissions, impatience,    exploratory “spike”
1 core    for100 hours
100 cores   for 1 hour
10k cores    in45 minutes
Unconstrained   by cost
Optimising for    price
On-demand
Reservedcapacity
1&year&term&                 Usage Fee    One-time Fee       Total        SavingsOption 1           $1493             -   ...
3&years&term&                 Usage Fee     One-time Fee       Total       SavingsOption 1          $4479             -   ...
450"                         On#Demand#                    1*year#RI#                  3*year#RI#   400"   350"   300"   2...
Spot InstancesHands-on
Placeholder
On-demand + Reserved +    Spot
“20th Centuryarchitectures”
Driven by analysis metrics
Increasing usability
AmazonMachine Image
Community  AMIs
http://www.cloudbiolinux.com/
http://usegalaxy.org/cloud
Reproducibility
Detailedlogging For S3 access
Application loggingArchive to S3 for durability
Automation
Application tierCode   Configuration
Application tierCode   Configuration
Application tier       Code           Configuration                                         Service tier                   ...
Application tier       Code           Configuration                                         Service tier                   ...
Application tier        Code                    Configuration                                                        Servic...
Value bakedinto each tier
Service tierConfiguration & optimization    Technology choices
Infrastructure      tierArchitecture. Configuration.
Automationmaximises this value
CloudFormationHands-on
Template
TemplateDefines a full infrastructure stack
Auto-scaling                                      RDS  EC2        SNS                           SimpleDB  EBS             ...
Template   CloudFormation                            Provisioned                             resources
Complete     definitionAtomic, idempotent provisioning.
JSONDeclarative language
{    "AWSTemplateFormatVersion" : "2010-09-09",    "Description" : "Create an EC2 instances",    "Parameters" : {       "K...
{    "AWSTemplateFormatVersion" : "2010-09-09",    "Description" : "Create an EC2 instances",                             ...
BootstrapHands-on
Chef & Puppet
Hands-on
Elastic MapReduceHands-on
Hadoop for dataintensive analytics
Painful at scale
S3Input data
S3        Input dataCode     Elastic       MapReduce
S3        Input dataCode     Elastic     Name       MapReduce     node
S3        Input dataCode     Elastic     Name       MapReduce     node                            Elastic                 ...
S3        Input dataCode     Elastic     Name       MapReduce     node                                      HDFS          ...
S3        Input dataCode     Elastic              Name       MapReduce              node                         Queries  ...
S3        Input dataCode     Elastic              Name                            Output       MapReduce              node...
S3 Input data  Elastic            OutputMapReduce          S3 + SimpleDB
Hands-on
SpotHands-on
Enablingcollaboration
Data
Lots of data
Lots of data,lots of uses
Lots of data,lots of uses,lots of users
Lots of data,   lots of uses,  lots of users,lots of locations
Forcemultipliers
Maximise value   of data
Data close to  compute
Import/Export
Direct Connect
AMIs,  Snapshots,CloudFormationHands-on
Public DatasetsHands-on
Ensuringsecurity
Sharedresponsibility
Requirementbased access
Certification
ISO 27001
SAS70 Type II
ServiceOrganisationControls (SOC     1) SSAE 16 and ISAE 3702
FISMA Moderate
HIPAA
ITARAWS GovCloud (US)
Data access  control  Detailed logging
Data stays local
Identity &Access ControlHands-on
Account
AccountDBA   Developer   Sys admin   Finance                                         Roles
AccountDBA   Developer   Sys admin   Finance                                         Roles      Sally      Robert         ...
Security credentials Multifactor authenticationManagement console access  Data read/write access      API level access
AccountDBA   Developer   Sys admin   Finance                                         Roles      Sally      Robert         ...
Networking controls
Virtual Private    Cloud
Virtual network    topology
IP address rangePublic and private subnetsRouting tablesNetwork gateways
Network access   control
Inbound ACLsOutbound ACLsIPsec VPN
Public subnetPublic facing website
Public subnet            Network ACLs + security groups                             Private subnetMulti-tier applications
Public subnet                          Private subnet            IPsec VPN                           On-premiseExtend your...
Private subnet            IPsec VPN                           On-premiseExtend your data centre
aws.amazon.com/security
End of Part One
cloudsupercomputing.net/         tutorial
aws.amazon.com/   awscredits
Part Two
Hands-on:Loosely coupledsystems
High scale,loosely coupled    system
Embarrassingly   parallel
Decoupled,  batchworkflows
TasksInstances
TasksQueueInstances
TasksQueueInstances
Tasks            Queue            Instances Increaseinstance   size
Tasks            Queue            Instances Increaseinstance   size
Tasks            Queue            Instances Increaseinstance  count
TasksQueueInstancesResultsStore
TasksQueueOn-premiseInstancesResultsStore
TasksQueueOn-premiseInstancesResultsStore
TasksQueueOn-premiseInstancesResultsStore
Batch     processingMonitoring. Auto-scaling. Queuing.        Spot. Automation.
Configure
150
Autoscaling.              Automation.Don’t forget to shut down your instances!
Hadoop with    Elastic  MapReduceNative. Streaming interface. Hive.          Spot with EMR.
Advanced EMR with MyrnaBioinformatics tools and large          datasets.  Thanks to Ben Langmead.
$100
CredentialsAccount -> Security CredentialsAccess key, secret key, account           number
AWS staff
cloudsupercomputing.net/         tutorial
Hands-on:ParallelComputation
Tightly coupled   systems
10 gig E
64 core parallel    clusterCC1. Custom AMI. EBS. Monitoring. MIT StarCluster. CloudFormation.
Multi-GPUCG1. CUDA 4. Compile & execute.    Benchmark against CPU.
OpenFOAMComputational Fluid Dynamics     with CC1 on EC2.
cloudsupercomputing.net/         tutorial
AGENDA  SC11 - Monday 14th November, 2011Cloud ConceptsBuilding BlocksTechnica l & Scientific ComputingL oosely coupled sys...
Understand theservices, tools andpatterns forbuildinghigh performancesystems in the
YOU ARE CORDIALLY INVITED TO THEAmazon Web Services              S C 11 B A S H    NETWORKING, DRINKS and GOODIES         ...
aws.amazon.com/about-aws/sc11
Thank you!
Questions & comments:matthew@amazon.co        m       @mza on Twitter
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Slides from the AWS tutorial at Supercomputing 2011. Related tutorial materials at: cloudsupercomputing.net

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  • Another example, also a hedge fund. Lot more spiky since they do High Frequency Trading\n
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  • High Performance Cloud Computing

    1. 1. HighPerformance Cloud ComputingSupercomputing 2011
    2. 2. Hello
    3. 3. Thank you
    4. 4. HPC withAWS
    5. 5. Understand theservices, tools andpatterns forbuildinghigh performancesystems in the
    6. 6. AGENDA SC11 - Monday 14th November, 2011Cloud ConceptsBuilding BlocksTechnica l & Scientific ComputingL oosely Coupled SystemsHands-on Session #1Parallel ComputationHands-on Session #2Wrap up
    7. 7. There Will Be Code
    8. 8. CloudConceptsA prelude
    9. 9. Consumer Seller business business
    10. 10. Decades of experience Operations, management and scale
    11. 11. Programmatic access
    12. 12. Unexpected innovation
    13. 13. Blinding flash of the obvious
    14. 14. Five years young
    15. 15. Infrastructure services
    16. 16. Compute Storage Placeholder ServicesDatabases & Support
    17. 17. Idea Results
    18. 18. Idea Results Heavy lifting
    19. 19. ScaleRedundancy Orchestrati on 70% Idea Results Heavy liftingCapacity Management Procurement
    20. 20. 30%Idea Results Infrastructure
    21. 21. Idea Results AWS
    22. 22. Idea Results AWS
    23. 23. Five things Iwish I’d knownwhen Iwas gettingstarted.
    24. 24. 1: Signing up
    25. 25. On the web
    26. 26. Free tier For new customers:aws.amazon.com/free
    27. 27. 750 hours of compute10Gb network attached storage5Gb object storage750 hours of computeKey/value store, notifications,messaging
    28. 28. 2: Interacting
    29. 29. HTTP, REST, SOAP
    30. 30. API driven HTTP, REST, SOAP
    31. 31. CLI
    32. 32. ec2-run-instances
    33. 33. ec2-terminate-instances
    34. 34. Java, Python, Ruby, .Net, PHP, iOS and Android
    35. 35. SDKJava, Python, Ruby, .Net, PHP, iOS and Android
    36. 36. Management console
    37. 37. Linux
    38. 38. Certificate-based root access
    39. 39. mza$ ssh -i web/us-east/aws-web.pemroot@ec2-204-236-247-169.compute-1.amazonaws.comLast login: Wed Jun 22 11:15:20 2011 from 82.26.6.99 __| __|_ ) CentOS _| ( / v5.4 ___|___|___| HVMx64 Welcome to an EC2 Public Image :-)[root@ip-10-17-135-244 ~]#
    40. 40. Windows
    41. 41. Administrator access
    42. 42. 3: Storage options
    43. 43. Ephemeral storage
    44. 44. Included with compute Ephemeral storage Lost at Not backedterminatio up n
    45. 45. When it’s gone, it’s gone
    46. 46. Hands-on
    47. 47. Elastic Block StoreHands-on
    48. 48. Network Mount as attached volumeElastic Block StoreSnapshot Persistent
    49. 49. Hands-on
    50. 50. S3Hands-on
    51. 51. Highly Highlydurable available S3 Tolerant to two simultaneo
    52. 52. durability
    53. 53. 99.999999999% durability
    54. 54. Objects in S3Billions of objects 556B 600 450 300 150 0 Q4 2006 Q4 2007 Q4 2008 Q4 2009 Q4 2010 Q3 2011
    55. 55. 370,000 peaktransactions per second
    56. 56. Payment options
    57. 57. Pay as you go
    58. 58. Gb/month
    59. 59. ECU/hour
    60. 60. No minimum
    61. 61. No subscriptions
    62. 62. Pricing tiers
    63. 63. Consolidated billing
    64. 64. Options
    65. 65. On-demand
    66. 66. Reservedcapacity
    67. 67. Hands-on
    68. 68. Spot MarketHands-on
    69. 69. Bandwidth
    70. 70. Free inbound
    71. 71. Import/Export
    72. 72. Reducedoutbound
    73. 73. Pricing calculator
    74. 74. aws.amazon.com/calculator
    75. 75. 5. Availability Zones
    76. 76. us-east-1 us-west-1 us-west-2us-gov-west-1 eu-west-1ap-southeast-1ap-northeast-1
    77. 77. eu-west-1aeu-west-1b eu-west-1c
    78. 78. BuildingblocksservicesFoundational
    79. 79. Compute
    80. 80. Elastic Compute Cloud
    81. 81. EC2Elastic Compute Cloud
    82. 82. Hands-on
    83. 83. Elastic compute infrastructureHands-on
    84. 84. ECU:Equivalent to 1.0 - 1.2 GHz 2007 Opteron or 2007 Xeon
    85. 85. ECU:EC2 Compute UnitEquivalent to 1.0 - 1.2 GHz 2007 Opteron or 2007 Xeon
    86. 86. Instance types
    87. 87. ClustMicro er$0.02 $2.10
    88. 88. Standard (m1) 1 ECU. 1.7 Gb memory. 160 Gb ephemeral storage.
    89. 89. High memory (m2)Up to 26 ECU. 8 cores. 68.4 Gb memory. 1.69 Tb ephemeral storage.
    90. 90. High CPU (c1)Up to 20 ECU. 8 cores. 7 Gb memory. 1.69 Tb ephemeral storage.
    91. 91. Higherperformance
    92. 92. MPI workloads
    93. 93. Bandwidth intensive
    94. 94. Hands-on
    95. 95. CC:Cluster ComputeHands-on
    96. 96. 2 x Intel Xeon 557023 Gb memory 1.7 Tb disk 33.5 ECUs
    97. 97. HVM
    98. 98. 10 gig E
    99. 99. Placement groups
    100. 100. Full bisectional bandwidth
    101. 101. Linpack
    102. 102. November 2010Cores 7040 R max 41.82 R peak 82.51
    103. 103. November 2010 231
    104. 104. June 2011451
    105. 105. November 2011
    106. 106. November 2011 42
    107. 107. WIEN2K Parallel Performance H size 56,000 (25GB) Runtime (16x8 processors) Local (Infiniband) 3h:48 Cloud (10Gbps) 1h:30 ($40) 1200 atom unit cell; SCALAPACK+MPI diagonalization, matrix size 50k-100kCredit: K. Jorissen, F. D. Villa, and J. J. Rehr (U. Washington)
    108. 108. GPU computation
    109. 109. Hands-on
    110. 110. CG:Cluster Compute with gpGPUHands-on
    111. 111. 2 x NVIDIA M2050
    112. 112. 2 x Intel Xeon 5570 23 Gb memory 1.7 Tb disk 2 x NVIDIA M2050
    113. 113. Flexible cluster control
    114. 114. API
    115. 115. Hands-on
    116. 116. SGEHands-on
    117. 117. LSF
    118. 118. Condor
    119. 119. Rocks+
    120. 120. Slurm
    121. 121. Included with all instances and block storage
    122. 122. CloudWatchIncluded with all instances and block storage
    123. 123. Custom metrics
    124. 124. Storage
    125. 125. Simple Storage Service
    126. 126. S3Simple Storage Service
    127. 127. Files in directories
    128. 128. Objects in buckets
    129. 129. http://s3.amazonaws.com/bucketname/objectid http://bucketname.s3.amazonaws.com/objectid
    130. 130. https://s3.amazonaws.com/bucketname/objectidhttps://bucketname.s3.amazonaws.com/objectid
    131. 131. 5Tb
    132. 132. Large object support 5Tb
    133. 133. Parallel uploads
    134. 134. Import/Export
    135. 135. Managedencryption
    136. 136. 99.99% durability
    137. 137. Reducedredundancy storage99.99% durability
    138. 138. Elastic Block Store
    139. 139. EBSElastic Block Store
    140. 140. Flexible, off-instance block storage
    141. 141. 1Gb to 1Tb
    142. 142. Scalable1Gb to 1Tb
    143. 143. Exposed as a device
    144. 144. Attached to arunning instance Exposed as a device
    145. 145. Snapshot to S3
    146. 146. Hands-on
    147. 147. Public DatasetsHands-on
    148. 148. Databases
    149. 149. Databases on EC2
    150. 150. Oracle and MySQL
    151. 151. Managed. High availability. Read replicas.
    152. 152. RelationalDatabase ServiceManaged. High availability. Read replicas.
    153. 153. High scale. Highly available. Key/attribute store
    154. 154. SimpleDBHigh scale. Highly available. Key/attribute store
    155. 155. No server toprovision or manage.
    156. 156. Perfect formetadata
    157. 157. Messaging &notifications
    158. 158. Hands-on
    159. 159. Simple Queue ServiceHands-on
    160. 160. Hands-on
    161. 161. Simple Notification ServiceHands-on
    162. 162. Technical &ScientificComputing
    163. 163. Elasticity
    164. 164. Research is bursty
    165. 165. Traditionalcapacity is static
    166. 166. Capacity Predicted capacity Estimated demand Time
    167. 167. Capacity Infrastructure Infrastructure Investment Estimated demand Barrier to entry Time
    168. 168. Capacity Infrastructure Real demand Time
    169. 169. Capacity Elastic capacity Real demand Time
    170. 170. Rapid response
    171. 171. Removingconstraints
    172. 172. Research isconstrained
    173. 173. Constrained by static infrastructure
    174. 174. Unconstrained
    175. 175. Larger systems,more molecules, more stars, higher order species...
    176. 176. Unconstrained by scale
    177. 177. 30,000 cores
    178. 178. Unconstrained by timeUpcoming conference, grant submissions, impatience, exploratory “spike”
    179. 179. 1 core for100 hours
    180. 180. 100 cores for 1 hour
    181. 181. 10k cores in45 minutes
    182. 182. Unconstrained by cost
    183. 183. Optimising for price
    184. 184. On-demand
    185. 185. Reservedcapacity
    186. 186. 1&year&term& Usage Fee One-time Fee Total SavingsOption 1 $1493 - $1493 -On-Demand onlyOption 2 $1008 $227 $1234 ~20%On-Demand +ReservedOption 3 $528 $455 $983 ~35%All reserved Total&Cost&for&1&Year.term&of&2&applica4on&servers,&steady&state&usage&
    187. 187. 3&years&term& Usage Fee One-time Fee Total SavingsOption 1 $4479 - $4479 -On-Demand onlyOption 2 $3024 $350 $3374 ~30%On-Demand +ReservedOption 3 $1584 $700 $2284 ~50%All reserved Total&Cost&for&3&Year.term&of&2&applica4on&servers,&steady&state&usage&
    188. 188. 450" On#Demand# 1*year#RI# 3*year#RI# 400" 350" 300" 250" 200" 2 150" 100" 50" 1 0" 1" 2" 3" 4" 5" 6" 7" 8" 9" 10" 11" 12" 13" 14" 15" 16" 17" 18" 19" 20" 21" 22" 23" 24"on-demand vs. reserved instances
    189. 189. Spot InstancesHands-on
    190. 190. Placeholder
    191. 191. On-demand + Reserved + Spot
    192. 192. “20th Centuryarchitectures”
    193. 193. Driven by analysis metrics
    194. 194. Increasing usability
    195. 195. AmazonMachine Image
    196. 196. Community AMIs
    197. 197. http://www.cloudbiolinux.com/
    198. 198. http://usegalaxy.org/cloud
    199. 199. Reproducibility
    200. 200. Detailedlogging For S3 access
    201. 201. Application loggingArchive to S3 for durability
    202. 202. Automation
    203. 203. Application tierCode Configuration
    204. 204. Application tierCode Configuration
    205. 205. Application tier Code Configuration Service tier Integration Operating system settings Services +Launch configuration configuration
    206. 206. Application tier Code Configuration Service tier Integration Operating system settings Services +Launch configuration configuration
    207. 207. Application tier Code Configuration Service tier Integration Operating system settings Services +Launch configuration configuration Infrastructure tier AMIs Architecture Multi-AZScaling rules Security groups Middleware
    208. 208. Value bakedinto each tier
    209. 209. Service tierConfiguration & optimization Technology choices
    210. 210. Infrastructure tierArchitecture. Configuration.
    211. 211. Automationmaximises this value
    212. 212. CloudFormationHands-on
    213. 213. Template
    214. 214. TemplateDefines a full infrastructure stack
    215. 215. Auto-scaling RDS EC2 SNS SimpleDB EBS SQS ResourcesElastic Beanstalk CloudWatch Security groups Tags
    216. 216. Template CloudFormation Provisioned resources
    217. 217. Complete definitionAtomic, idempotent provisioning.
    218. 218. JSONDeclarative language
    219. 219. { "AWSTemplateFormatVersion" : "2010-09-09", "Description" : "Create an EC2 instances", "Parameters" : { "KeyName" : { "Description" : "Name of an existing EC2 KeyPair to enable SSH access to the instance", "Type" : "String" } }, "Mappings" : { "RegionMap" : { "us-east-1" : { "AMI" : "ami-76f0061f" }, "us-west-1" : { "AMI" : "ami-655a0a20" }, "eu-west-1" : { "AMI" : "ami-7fd4e10b" }, "ap-southeast-1" : { "AMI" : "ami-72621c20" }, "ap-northeast-1" : { "AMI" : "ami-8e08a38f" } } }, "Resources" : { "Ec2Instance" : { "Type" : "AWS::EC2::Instance", "Properties" : { "KeyName" : { "Ref" : "KeyName" }, "ImageId" : { "Fn::FindInMap" : [ "RegionMap", { "Ref" : "AWS::Region" }, "AMI" ]}, "UserData" : { "Fn::Base64" : "80" } } } }, "Outputs" : { "InstanceId" : { "Description" : "InstanceId of the newly created EC2 instance", "Value" : { "Ref" : "Ec2Instance" } }, "AZ" : { "Description" : "Availability Zone of the newly created EC2 instance", "Value" : { "Fn::GetAtt" : [ "Ec2Instance", "AvailabilityZone" ] } }, "PublicIP" : { "Description" : "Public IP address of the newly created EC2 instance", "Value" : { "Fn::GetAtt" : [ "Ec2Instance", "PublicIp" ] } } }}
    220. 220. { "AWSTemplateFormatVersion" : "2010-09-09", "Description" : "Create an EC2 instances", Headers Parameters "Parameters" : { "KeyName" : { "Description" : "Name of an existing EC2 KeyPair to enable SSH access to the instance", "Type" : "String" } }, "Mappings" : { "RegionMap" : { "us-east-1" : { "AMI" : "ami-76f0061f" }, "us-west-1" : { Mappings "AMI" : "ami-655a0a20" }, "eu-west-1" : { "AMI" : "ami-7fd4e10b" }, "ap-southeast-1" : { "AMI" : "ami-72621c20" }, "ap-northeast-1" : { "AMI" : "ami-8e08a38f" } } }, "Resources" : { "Ec2Instance" : { "Type" : "AWS::EC2::Instance", Resources "Properties" : { "KeyName" : { "Ref" : "KeyName" }, "ImageId" : { "Fn::FindInMap" : [ "RegionMap", { "Ref" : "AWS::Region" }, "AMI" ]}, "UserData" : { "Fn::Base64" : "80" } } } }, "Outputs" : { "InstanceId" : { "Description" : "InstanceId of the newly created EC2 instance", "Value" : { "Ref" : "Ec2Instance" } }, Outputs "AZ" : { "Description" : "Availability Zone of the newly created EC2 instance", "Value" : { "Fn::GetAtt" : [ "Ec2Instance", "AvailabilityZone" ] } }, "PublicIP" : { "Description" : "Public IP address of the newly created EC2 instance", "Value" : { "Fn::GetAtt" : [ "Ec2Instance", "PublicIp" ] } } }}
    221. 221. BootstrapHands-on
    222. 222. Chef & Puppet
    223. 223. Hands-on
    224. 224. Elastic MapReduceHands-on
    225. 225. Hadoop for dataintensive analytics
    226. 226. Painful at scale
    227. 227. S3Input data
    228. 228. S3 Input dataCode Elastic MapReduce
    229. 229. S3 Input dataCode Elastic Name MapReduce node
    230. 230. S3 Input dataCode Elastic Name MapReduce node Elastic cluster
    231. 231. S3 Input dataCode Elastic Name MapReduce node HDFS Elastic cluster
    232. 232. S3 Input dataCode Elastic Name MapReduce node Queries HDFS + BI Via JDBC, Pig, Hive Elastic cluster
    233. 233. S3 Input dataCode Elastic Name Output MapReduce node S3 + SimpleDB Queries HDFS + BI Via JDBC, Pig, Hive Elastic cluster
    234. 234. S3 Input data Elastic OutputMapReduce S3 + SimpleDB
    235. 235. Hands-on
    236. 236. SpotHands-on
    237. 237. Enablingcollaboration
    238. 238. Data
    239. 239. Lots of data
    240. 240. Lots of data,lots of uses
    241. 241. Lots of data,lots of uses,lots of users
    242. 242. Lots of data, lots of uses, lots of users,lots of locations
    243. 243. Forcemultipliers
    244. 244. Maximise value of data
    245. 245. Data close to compute
    246. 246. Import/Export
    247. 247. Direct Connect
    248. 248. AMIs, Snapshots,CloudFormationHands-on
    249. 249. Public DatasetsHands-on
    250. 250. Ensuringsecurity
    251. 251. Sharedresponsibility
    252. 252. Requirementbased access
    253. 253. Certification
    254. 254. ISO 27001
    255. 255. SAS70 Type II
    256. 256. ServiceOrganisationControls (SOC 1) SSAE 16 and ISAE 3702
    257. 257. FISMA Moderate
    258. 258. HIPAA
    259. 259. ITARAWS GovCloud (US)
    260. 260. Data access control Detailed logging
    261. 261. Data stays local
    262. 262. Identity &Access ControlHands-on
    263. 263. Account
    264. 264. AccountDBA Developer Sys admin Finance Roles
    265. 265. AccountDBA Developer Sys admin Finance Roles Sally Robert Users Chris
    266. 266. Security credentials Multifactor authenticationManagement console access Data read/write access API level access
    267. 267. AccountDBA Developer Sys admin Finance Roles Sally Robert Users Chris
    268. 268. Networking controls
    269. 269. Virtual Private Cloud
    270. 270. Virtual network topology
    271. 271. IP address rangePublic and private subnetsRouting tablesNetwork gateways
    272. 272. Network access control
    273. 273. Inbound ACLsOutbound ACLsIPsec VPN
    274. 274. Public subnetPublic facing website
    275. 275. Public subnet Network ACLs + security groups Private subnetMulti-tier applications
    276. 276. Public subnet Private subnet IPsec VPN On-premiseExtend your data centre
    277. 277. Private subnet IPsec VPN On-premiseExtend your data centre
    278. 278. aws.amazon.com/security
    279. 279. End of Part One
    280. 280. cloudsupercomputing.net/ tutorial
    281. 281. aws.amazon.com/ awscredits
    282. 282. Part Two
    283. 283. Hands-on:Loosely coupledsystems
    284. 284. High scale,loosely coupled system
    285. 285. Embarrassingly parallel
    286. 286. Decoupled, batchworkflows
    287. 287. TasksInstances
    288. 288. TasksQueueInstances
    289. 289. TasksQueueInstances
    290. 290. Tasks Queue Instances Increaseinstance size
    291. 291. Tasks Queue Instances Increaseinstance size
    292. 292. Tasks Queue Instances Increaseinstance count
    293. 293. TasksQueueInstancesResultsStore
    294. 294. TasksQueueOn-premiseInstancesResultsStore
    295. 295. TasksQueueOn-premiseInstancesResultsStore
    296. 296. TasksQueueOn-premiseInstancesResultsStore
    297. 297. Batch processingMonitoring. Auto-scaling. Queuing. Spot. Automation.
    298. 298. Configure
    299. 299. 150
    300. 300. Autoscaling. Automation.Don’t forget to shut down your instances!
    301. 301. Hadoop with Elastic MapReduceNative. Streaming interface. Hive. Spot with EMR.
    302. 302. Advanced EMR with MyrnaBioinformatics tools and large datasets. Thanks to Ben Langmead.
    303. 303. $100
    304. 304. CredentialsAccount -> Security CredentialsAccess key, secret key, account number
    305. 305. AWS staff
    306. 306. cloudsupercomputing.net/ tutorial
    307. 307. Hands-on:ParallelComputation
    308. 308. Tightly coupled systems
    309. 309. 10 gig E
    310. 310. 64 core parallel clusterCC1. Custom AMI. EBS. Monitoring. MIT StarCluster. CloudFormation.
    311. 311. Multi-GPUCG1. CUDA 4. Compile & execute. Benchmark against CPU.
    312. 312. OpenFOAMComputational Fluid Dynamics with CC1 on EC2.
    313. 313. cloudsupercomputing.net/ tutorial
    314. 314. AGENDA SC11 - Monday 14th November, 2011Cloud ConceptsBuilding BlocksTechnica l & Scientific ComputingL oosely coupled systemsHands-on Session #1Parallel computationHands-on Session #2Wrap up, drinks
    315. 315. Understand theservices, tools andpatterns forbuildinghigh performancesystems in the
    316. 316. YOU ARE CORDIALLY INVITED TO THEAmazon Web Services S C 11 B A S H NETWORKING, DRINKS and GOODIES BOOTH #6202
    317. 317. aws.amazon.com/about-aws/sc11
    318. 318. Thank you!
    319. 319. Questions & comments:matthew@amazon.co m @mza on Twitter

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