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building global softwareearthcube sciencecloud
Ian FosterArgonne National LaboratoryUniversity of [email protected]
all software must be global software*
Rhys Francis
Globus endpoints, Azimuthal Equidistant projection* “all” of course doesn’t mean 100%
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 [email protected]"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
research data management as a service
research data management as a service
identity, group management as a service
8,000 endpoints and 25,000 users10B 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 reduced cost
broad adoption of SaaS in science requires science platforms
Globus endpoints, Azimuthal Equidistant projection
three questionswhat 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, [email protected] endpoints, Azimuthal Equidistant projection
