University of California, Berkeley professor Armando Fox, co-founder of the Reliable, Adaptive, and Distributed Systems Laboratory, co-wrote a paper that outlined some early challenges and advantages of high performance computing (HPC) clouds. He says in an interview that "there's a huge and largely untapped 'new middle class' of scientific computing users who would immediately benefit from running medium-to-large jobs on public clouds."
Among the reasons for this is the fact that experiments on the public cloud can go faster because the provisioning of virtualized machines is quick and obviates the need for users to wait for their turn to use computer resources, while cost associativity also is realized.
Although Fox acknowledges that the current cloud computing architecture may not be appropriate for all scientific computing users, he says that much can be done to customize cloud offerings to HPC.
"And the exciting part here is that because of the scale and volume of commodity clouds, scientific computing users have a chance to do something they've never really had before—to influence the design of commodity equipment," Fox notes. He projects that cloud computing will be the sole means for performing big data analytics.
From HPC in the Cloud
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