AWS Cloud for HPC and Big Data



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Transcription:

AWS Cloud for HPC and Big Data David Pellerin, Business Development Principal IDC HPC User Forum September 16, 2014

AWS Regions US West (Oregon) US West (Northern California) GovCloud (ITAR Compliance) US East (Northern Virginia) EU (Ireland) China (Beijing) Asia Pacific (Tokyo) AWS Regions (10) South America (Sao Paulo) Asia Pacific (Singapore) Asia Pacific (Sydney) AWS Edge Locations (52)

Customer Applications Development & Deployment Monitoring CloudWatch Application Services Foundation Services RDS Databases Dynamo AWS Global Infrastructure Applications AWS Global Infrastructure SES SNS SQS Compute BeanStalk Deployment & Management OpsWork Elastic Transcoder CloudSearch SWF ElastiCache RedShift EMR DataPipeline Kinesis AWS Global Infrastructure Storage Cloud Formation Analytics CloudTrail IAM Networking Identity & Access Federation AppStream Content Delivery CloudFront API Human Interaction Support Interaction AWS Globa Web Console l Command Line Infras Libraries, SDK s truct ure EC2 WorkSpaces S3 EBS Glacier Storage Gateway VPC Direct Connect ELB Route53 Regions AWS Global Availability Infrastructure Zones Edge Locations AWS Global Infrastructure

EC2 Instance Type History Increasing customer choice m1.small new existing m1.xlarge m1.large m1.small 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 cr1.8xlarge hs1.8xlarge m3.xlarge m3.2xlarge hi1.4xlarge m1.medium cc2.8xlarge cg1.4xlarge t1.micro m2.xlarge m2.2xlarge m2.4xlarge c1.medium c1.xlarge m1.xlarge m1.large m1.small t2.micro t2.small t2.medium t1.micro hs1.8xlarge m3.xlarge m3.2xlarge hi1.4xlarge m1.medium cc2.8xlarge cr1.8xlarge cg1.4xlarge m2.xlarge m2.2xlarge m2.4xlarge c1.medium c1.xlarge m1.xlarge m1.large m1.small g2.2xlarge hs1.xlarge hs1.2xlarge hs1.4xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge m3.medium m3.large i2.large i2.xlarge i2.4xlarge i2.8xlarge r3.large r3.xlarge r3.2xlarge r3.4xlarge r3.8xlarge 2006 2007 2008 2009 2010 2011 2012-2013 September, 2014

Multiple Purchase Models On-Demand Pay for compute capacity by the hour with no long-term commitments For spiky workloads, or to define needs Reserved Make a low, one-time payment and receive a significant discount on the hourly charge For committed utilization Spot Bid for unused capacity, charged at a Spot Price which fluctuates based on supply and demand For time-insensitive or transient workloads AWS Spot is a game-changer for HPC

Motivators for HPC in the Cloud Cloud for HPC Scalability Cloud for Secure Global Collaboration Cloud for Big Data

HGST application roadmap: Molecular dynamics CAD, CFD, EDA Collaboration tools for engineering Big data for manufacturing yield analysis, including Amazon Redshift HGST is using AWS for a higher performance, lower cost, faster deployed solution vs buying a huge on-site cluster. - Steve Philpott, CIO

On AWS, deploy multiple clusters running at the same time and match the architectures to the jobs

Use automation to manage cluster sizing and monitor jobs and costs AWS Auto Scaling can work with existing HPC scheduling software

Many HPC Deployment Methods Traditional HPC schedulers and cluster managers Born in the cloud tools MIT StarCluster Cycle Computing CycleServer AWS-provided tools and APIs Cloudformation, Auto Scaling cfncluster (github.com/awslabs/cfncluster) For many use-cases

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Bristol-Myers Squibb Clinical Trials on AWS # of Simulations # of Servers Total Run Time (hr) On-Premises 2000 2 60 Cloud 2000 256 1.2 Clinical trial simulations took 98% less time More efficient and iterative simulations results in fewer human trials 64% savings on clinical trial costs We re using fewer subjects in these trials, and needing fewer blood samples. Russell Towell Senior Solutions Specialist

Collaboration and Design in the Cloud Cross-functional collaboration app Helps design around manufacturing Allows users to define how they work Users can spin-up their own environments people devices design This could change the way manufacturing is architected. Industrial manufacturing Joe Salvo Manager, Business Integration Technologies Laboratory software

Enabling Global Collaboration Bring the users to the data, don t send the data to the users

Thin Client Remote Collaboration Calgary Scientific PureWeb www.calgaryscientific.com/resolutionmd/web/ demos.getpureweb.com/

Amazon AppStream Application Streaming Remote visualization Thin client 3D applications

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AWS Has Always Been About Big Data

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Big Data for Genome Analysis Baylor College of Medicine, Amazon Web Services, and DNAnexus: cloud-based analysis of genomic data from over 14,000 patients

Big Data is Everywhere!

Summary Cloud for Scalability Cloud for Global Collaboration Cloud for Big Data

Thank You