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building global software
earthcube  sciencecloud
Ian Foster
Argonne National Laboratory
University of Chicago
foster@uchi...
all software
must be
global software*
Rhys Francis
Globus endpoints, Azimuthal Equidistant projection* “all” of course doe...
automation ✦ economies of scale
simplicity ✦ network effects
7
data locations in
a study of breast
cancer genomics
some identities required for Dark Energy Survey
(Don Petravick)
CLI = "ssh ian@cli.globusonline.org"
def transfer(from, to):
id = run( CLI + " transfer --generate-id" )
p = run( CLI + " ...
research data management as a service
research data management as a service
identity, group management as a service
8,000 endpoints and 25,000 users
10B files and 95 PB moved
Globus endpoints, Mercator projection
science cloud platforms
can accelerate service
development
science cloud platforms
can accelerate service
development
three take home messages
all software must be global software
Software-as-a-service (SaaS) allows for
global impact at red...
three questions
what activity in your research is the
most painful and time-consuming?
what data management activities can...
building global software/earthcube->sciencecloud
building global software/earthcube->sciencecloud
building global software/earthcube->sciencecloud
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building global software/earthcube->sciencecloud

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My lunchtime talk at the EarthCube all hands meeting. I made the case that we need to rethink how science software is developed and delivered, leveraging the software-as-a-service (SaaS) methods that have proved so successful in industry to reduce both costs and barriers to use. [The beautiful (IMHO) maps were created by me with Python matplotlib, showing the locations of (a subset of) Globus endpoints.]

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building global software/earthcube->sciencecloud

  1. 1. building global software earthcube  sciencecloud Ian Foster Argonne National Laboratory University of Chicago foster@uchicago.edu
  2. 2. all software must be global software* Rhys Francis Globus endpoints, Azimuthal Equidistant projection* “all” of course doesn’t mean 100%
  3. 3. automation ✦ economies of scale simplicity ✦ network effects
  4. 4. 7 data locations in a study of breast cancer genomics
  5. 5. some identities required for Dark Energy Survey (Don Petravick)
  6. 6. CLI = "ssh ian@cli.globusonline.org" def transfer(from, to): id = run( CLI + " transfer --generate-id" ) p = run( CLI + " transfer --taskid " + id + " -- " + from + " " + to) if p != None: (stdout, stderr) = run( CLI + " wait -q " + id) dp = run( CLI + " details -f status -O csv " + id) if dp != None: return ( dp, stderr, stdout ) research data management as a service
  7. 7. research data management as a service
  8. 8. research data management as a service
  9. 9. identity, group management as a service
  10. 10. 8,000 endpoints and 25,000 users 10B files and 95 PB moved Globus endpoints, Mercator projection
  11. 11. science cloud platforms can accelerate service development
  12. 12. science cloud platforms can accelerate service development
  13. 13. three take home messages all software must be global software Software-as-a-service (SaaS) allows for global impact at reduced cost broad adoption of SaaS in science requires science platforms Globus endpoints, Azimuthal Equidistant projection
  14. 14. three questions what activity in your research is the most painful and time-consuming? what data management activities can you imagine outsourcing? do you use Globus services? If not, why not?  Ian Foster, foster@uchicago.edu Globus endpoints, Azimuthal Equidistant projection

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