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Except for the folks at Cray, most people are unaware of the unique requirements that set apart supercomputing infrastructure from cloud computing infrastructure. In its simplest form the difference is between latency and capacity. For business intelligence applications such as optimization and logistics many servers are required to solve a single problem, and low latency communication between the servers is instrumental for performance. The intuition behind this is easy to understand: a modern microprocessor executes 4-5 instructions per 250ps, and thus packet latencies of 10GbE, (between 5-50usec), are roughly equivalent to 100k to 1M processor instructions. If a processor is dependent on the results computed by another processor, it will have to idle till the data is available. Cumulatively, across a couple hundred servers, this can lead to peak performance that is only 1-5% of peak.

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The take-away of this project is echoing the findings in the missing middle reports for digital manufacturing. There is tremendous opportunity for SMBs to improve business operations by leveraging the same techniques as their enterprise brethren. But the cost of commercial software for HPC is not consistent with the value provided for SMBs. Furthermore, the IT and operational skills required both to setup and manage a supercomputing infrastructure is beyond the capabilities of most SMBs. On-demand HPC services, as we have demonstrated with the supers in Beijing and Shanghai, can overcome many of these issues. Most importantly, it enables a new level of innovation by domain experts, such as professors and independent consultants, who do have the skills necessary to leverage supercomputing techniques, but up to now have not had access to public supercomputing capability and services.

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