The Urban Institute chose a cloud-first strategy with AWS to increase the capacity and performance of big data and high-performance computing workloads for 300+ researchers. In this chalk talk, we demonstrate how our team piloted the execution of one of our signature microsimulation models in parallel, designing a new architecture in the cloud that required minimal changes to the original model’s source code. We also  show how our team worked directly with AWS to develop open source code that launches powerful Amazon Elastic MapReduce (Amazon EMR) Spark clusters with minimal setup time, and combined it with our Elastic Cloud Computing Environment to allow for a simple Spark user experience.

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Provide Faster, Scalable Solutions to
Support Research Use Cases with AWS
Graham MacDonald
Urban Institute
W P S 3 1 0
Rodney Grilli
AWS

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Agenda
About Urban
Our vision: The next generation of policy
analysis
Our problem: Massive, decades-old code
Our AWS Solution: High level technical overview
Audience-driven deep dive(s)

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The Urban Institute

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“What if?” policy analysis

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The next generation of policy analysis

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Massive, decades-old code
Long history of “what if?” modeling
Built in the 1970s and 1980s
Many written in Fortran
10,000s to 100,000s of lines of code
Expensive, difficult to change

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The solution

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17. Thank you!
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Graham MacDonald &
Rodney Grilli

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