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DTSTAMP:20190731T213557Z
LOCATION:Crystal Foyer and Crystal B
DTSTART;TZID=America/Chicago:20190730T183000
DTEND;TZID=America/Chicago:20190730T203000
UID:pearc_PEARC19_sess157_pos155@linklings.com
SUMMARY:Scaling R Shiny Apps to Multiple Concurrent Users in a Secured HPC
  Environment Using Open OnDemand
DESCRIPTION:Scaling R Shiny Apps to Multiple Concurrent Users in a Secured
  HPC Environment Using Open OnDemand\n\nFranz, Gadepalli, Pietrzak, Ozer, 
 Webb...\n\nOpen OnDemand is an open source project to provide web based ac
 cess to HPC resources (https://openondemand.org). OnDemand’s “Interactive 
 Apps” support launching web applications like Jupyter and RStudio on clust
 er compute nodes, proxying HTTP requests to those apps, and secure user se
 paration of both app and data access enforced at the OS level. This paper 
 describes leveraging OnDemand to enable the deployment of R Shiny applicat
 ions that can be launched in OnDemand’s interactive HPC environment by mul
 tiple analysts at the same time to visualize different datasets. Dataset a
 nd app authorization is managed using network file system (NFS) file acces
 s lists (ACLs). A custom OnDemand app was built to enable admins to manage
  who has access to specific apps and what datasets can be loaded by those 
 apps. By using OnDemand to facilitate the use of an HPC batch scheduler as
  the process manager and OnDemand as the proxy we can support multiple ana
 lysts launching Shiny apps to access their data in a scalable and secure m
 anner without the need for managing a separate dedicated installation of R
 Studio or Shiny Server.\n\nPosters\nReception, Poster
URL:https://pearc19.conference-program.com/presentation/?id=pos155&sess=se
 ss157
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