Scientific Computing with Amazon Web Services



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Transcription:

Scientific Computing with Amazon Web Services Jamie Kinney Director of Scientific Computing Amazon Web Services jkinney@amazon.com @jamiekinney

AWS Scientific Computing Team Focus Global Big Science Projects Enabling the long tail of science Collaborative research Education for our customers, Amazonians and Policy Makers Initial focus on: -Life Sciences -Earth Sciences -Astronomy/Astrophysics -High Energy Physics -Materials Science

Why are we focusing on the Scientific Community? In order to meaningfully change our world for the better by accelerating the pace of scientific discovery Scientific computing is a profitable business for AWS To develop new capabilities which will benefit all AWS customers - Streaming data processing & analytics - Exabyte scale data management solutions - Collaborative research tools and techniques - New AWS regions - Significant advances in low-power compute, storage and data centers - Identify efficiencies which will lower our costs and pricing for customers - Push our existing services to support exabyte/exaflop scale workloads

2004 2013 $7B retail business ~10,000 employees A whole lot of servers Every day, AWS adds enough server capacity to power this $7B enterprise

Said another way AWS is deploying the equivalent of a top-20 supercomputer every few days

One server running for 1000 hours has the same cost as 1000 servers running for one hour.

A Snapshot of AWS Global Capacity AZ Transit AZ AZ AZ AZ Transit 53 AWS Edge Locations 11 Regions 28 Availability Zones 2 or more AZs per Region 1-6 Data Centers per AZ 50,000-80,000+ servers per DC Up to 102 Tbps provisioned to each DC

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 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 2006 2007 2008 2009 2010 2011 2012-2013 2014 g2.2xlarge hs1.xlarge hs1.2xlarge hs1.4xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge m3.medium m3.large i2.large i2.xlarge i2.4xlarge i2.8xlarge r3.large r3.xlarge r3.2xlarge r3.4xlarge r3.8xlarge

C4 Instance Family Turbo to 3.5 Ghz on all cores 2.9GHz Haswell E5-2666 v3 up to 60 gb RAM Supports AVX2 https://aws.amazon.com/blogs/aws/now-availablenew-c4-instances/

AWS-ESNET Peering March 2015 John Hover - Brookhaven National Lab

AWS Egress Waiver for Researchers 2013: Initial trial in Australia for users connecting via AARNET and AAPT 2014: Extended the waiver to include ESNET and Internet2 2015: Extending support to other major NRENs: Terms: Waiving egress fees up to 15% of AWS bill, customers responsible for anything above this amount Majority of traffic must transit via NREN with no transit costs 15% waiver applies to aggregate usage for consolidated billing Does not apply to workloads for which the egress is the service we provide e.g. live video streaming, MOOCs, websites, etc

Scientific Computing Use Cases Science-as-a-Service Large-scale HTC (100,000+ core clusters) Large-scale MapReduce (Hadoop/Spark/Shark) using or EMR Small to medium-scale clusters (hundreds of nodes) for traditional MPI workloads Many small MPI clusters working in parallel to explore parameter space Small to medium scale GPGPU workloads Dev/test of MPI workloads prior to submitting to supercomputing centers Ephemeral clusters, custom tailored to the task at hand, created for various stages of a pipeline Collaborative research environments On-demand academic training/lab environments

Ames On-demand access to effectively limitless resources Specialized supercomputing resources NASA Researcher Small-scale shared compute

John Hover - Brookhaven National Lab

Globally Distributed Compute for LHC US Atlas

AWS Public Data Sets aws.amazon.com/datasets

AWS Research Grants AWS.amazon.com/grants

Thank You