high performance cloud computing
DESCRIPTION
Talk given at a customer site recentlyTRANSCRIPT
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High Performance
Deepak SinghP r i n c i p a l P r o d u c t M a n a g e r
Cloud Computing
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Via butteryflysha under a CC-BY license
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Image: Simon Cockell under CC-BY
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High Scale Computing
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using a large number of computers at the same time to solve a problem
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2
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High ThroughputComputing
1
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scale out
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“embarassingly parallel”
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constraints
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constrained by capacity
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constrained by capacity
More molecules
More simulations
More dimensions
Bigger systems
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constrained by time
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constrained by time
Upcoming conference
Grant submissions
Impatience!
Exploratory “spike” run
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EC2
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Elastic Compute Cloud
EC2
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elastic
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programmatic
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ec2-run-instances
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AWS CloudFormation
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EC2 instance types
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standard “m1”high cpu “c1”
high memory “m2”
http://aws.amazon.com/ec2/instance-types/
EC2
inst
ance
type
s
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standard “m1”high cpu “c1”
high memory “m2”
http://aws.amazon.com/ec2/instance-types/
EC2
inst
ance
type
s
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ec2-terminate-instances
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rapid provisioning
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10K in 45 minutes
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design patterns
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optimize for throughput
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Tasks
Instances
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Tasks
Instances
Queue
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Tasks
Instances
Queue
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vertical scaling
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Increase instance size
Tasks
Instances
Queue
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Increase instance size
Tasks
Instances
Queue
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horizontal scaling
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Increase instance count
Tasks
Instances
Queue
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Tasks
Instances
Queue
Results
Store
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Tasks
Instances
Queue
Results
Store
On-premise
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Tasks
Instances
Queue
Results
Store
On-premise
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Tasks
Instances
Queue
Results
Store
On-premise
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optimize for cost
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optimize for costmaximize bang for buck
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on-demand instances
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reserved instances
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spot instances
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ideal for batch
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persistent requests
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all or nothing
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use cases galore
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Credit: Angel Pizzaro, U. Penn
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ClusterComputing
2
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tightly coupled
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MPI
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Cluster Compute
Dual Intel X5570
“Nehalem”23GB RAM
HVM1.7TB scratch
GPGPU
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Cluster Compute
10 gig E
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PlacementGroup
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Cluster Compute
Placementgroup
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231
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450
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Cores 7040
Rmax 41.82
Rpeak 82.51
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GPGPU
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2 x Tesla
M2050
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Getting Started
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http://aws.amazon.com/hpc
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4 steps
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15 minutes
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performance
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WIEN2K Parallel Performance
H size 56,000 (25GB)Runtime (16x8 processors)
Local (Infiniband) 3h:48Cloud (10Gbps) 1h:30 ($40)
1200 atom unit cell; SCALAPACK+MPI diagonalization, matrix size 50k-100k
Credit: K. Jorissen, F. D. Villa, and J. J. Rehr (U. Washington)
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customer examples
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Computational Fluid Dynamics
Example Use Case #1
Dynamic Clusters
40-180 CC1 instances
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Molecular Dynamics
Example Use Case #2
Steady Usage
32-40 CG1 instances
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Machine Learning
Example Use Case #3
Spiky, Experimental
8-20 CG1 instances
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Customer Case Study: Bioproximity
http://aws.amazon.com/solutions/case-studies/bioproximity/
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Customer Case Study: cyclopic energy
http://aws.amazon.com/solutions/case-studies/cyclopic-energy/
OpenFOAM®
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Customer Case Study: PSR
http://aws.amazon.com/solutions/case-studies/psr/
44,000 CPU hrs in Oct 2010
Stochastic Dual Dynamic Programming
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familiar tools
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Oracle Grid Engine
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MIT StarCluster
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LSF
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Moab/Torque
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Condor
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StackIQ Rocks+
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Slurm
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[email protected] Twitter:@mndoci
http://slideshare.net/mndocihttp://mndoci.com
Inspiration and ideas from Matt Wood, James Hamilton
& Larry Lessig
Credit” Oberazzi under a CC-BY-NC-SA license