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High Performance Cloud Computing
 

High Performance Cloud Computing

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Talk given at a customer site recently

Talk given at a customer site recently

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    High Performance Cloud Computing High Performance Cloud Computing Presentation Transcript

    • High Performance Cloud Computing Deepak Singh P r i n c i p a l P r o d u c t M a n a g e r
    • Via butteryflysha under a CC-BY license
    • Image: Simon Cockell under CC-BY
    • High Scale Computing
    • using a large number ofcomputers at the sametime to solve a problem
    • 2
    • 1 High Throughput Computing
    • scale out
    • “embarassingly parallel”
    • constraints
    • constrained by capacity
    • More molecules Bigger systemsconstrained by capacity More simulations More dimensions
    • constrained by time
    • Upcoming conference Grant submissionsconstrained by time Impatience! Exploratory “spike” run
    • EC2
    • EC2Elastic Compute Cloud
    • elastic
    • programmatic
    • ec2-run-instances
    • AWS CloudFormation
    • EC2 instance types
    • s pe ty ce an standard “m1” st in 2EC high cpu “c1” high memory “m2” http://aws.amazon.com/ec2/instance-types/
    • s pe ty ce an standard “m1” st in 2EC high cpu “c1” high memory “m2” http://aws.amazon.com/ec2/instance-types/
    • ec2-terminate-instances
    • rapid provisioning
    • 10K in 45 minutes
    • design patterns
    • optimize forthroughput
    • TasksInstances
    • TasksQueueInstances
    • TasksQueueInstances
    • vertical scaling
    • Tasks Queue Instances Increaseinstance size
    • Tasks Queue Instances Increaseinstance size
    • horizontal scaling
    • Tasks Queue Instances Increaseinstance count
    • TasksQueueInstancesResultsStore
    • TasksQueueOn-premiseInstancesResultsStore
    • TasksQueueOn-premiseInstancesResultsStore
    • TasksQueueOn-premiseInstancesResultsStore
    • optimize for cost
    • optimize for cost maximize bang for buck
    • on-demand instances
    • reserved instances
    • spot instances
    • ideal for batch
    • persistent requests
    • all or nothing
    • use cases galore
    • Credit: Angel Pizzaro, U. Penn
    • 2 Cluster Computing
    • tightly coupled
    • MPI
    • Dua l Intel 23GB RA X 5570 GPGPU M“Neha lem” HVM 1.7TB scratch Cluster Compute
    • 10 gig E Cluster Compute
    • Placement Group
    • Placement groupCluster Compute
    • 231
    • 450
    • Cores 7040R max 41.82R peak 82.51
    • GPGPU
    • 2 x Tesla M2050
    • Getting Started
    • http://aws.amazon.com/hpc
    • 4 steps
    • 15 minutes
    • http://aws.amazon.com/ec2
    • performance
    • 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)
    • customer examples
    • Example Use Case #1Computational Fluid Dynamics Dynamic Clusters 40-180 CC1 instances
    • Example Use Case #2 Molecular Dynamics Steady Usage 32-40 CG1 instances
    • Example Use Case #3 Machine Learning Spiky, Experimental 8-20 CG1 instances
    • Customer Case Study: Bioproximity http://aws.amazon.com/solutions/case-studies/bioproximity/
    • Customer Case Study: cyclopic energy OpenFOAM® http://aws.amazon.com/solutions/case-studies/cyclopic-energy/
    • Customer Case Study: PSR Stochastic Dual Dynamic Programming 44,000 CPU hrs in Oct 2010 http://aws.amazon.com/solutions/case-studies/psr/
    • familiar tools
    • Oracle Grid Engine
    • MIT StarCluster
    • LSF
    • Moab/Torque
    • Condor
    • StackIQ Rocks+
    • Slurm
    • deesingh@amazon.com Twitter:@mndoci http://slideshare.net/mndoci http://mndoci.com Inspiration and ideas from Matt Wood, James Hamilton & Larry LessigCredit” Oberazzi under a CC-BY-NC-SA license