You can get away with those at large research universities.
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Power (especially if there is some kind of significant scientific facility on premise), space (especially in reused buildings), manpower (undergrads, grad students, post docs, professional post graduates), running old/reused hardware, etc.
The things that tend to be "cheap" on campuses: Simply saying "There's risk" is not sufficient - you must still make a compelling argument that the cost of avoiding that risk is justified, and you're not doing that. "No one on the team can eat red meat because it increases the risk of heart attack!"Īnd on and on and on. "The lab work must be done in a bomb shelter in case of war or tornados!" "The lead researcher shouldn't be allowed in a car because it might crash!" the only meaningful offering from the cloud is likely preventing data loss, and this can be done fairly well with a simple backup strategy.Īgain - they aren't a business where losing a few hours/days of customer data is potentially business ending.Īnd to be blunt - I can make the same risk avoidance claims about a lot of things that would simply get me laughed out of the room. There is no compelling reason to "scale" in the way that a company might need to in order to handle additional unexpected load from customers or hit marketing campaigns.īasically. They have real computation needs that mean hardware is unlikely to sit idle. They often have limited budgets that are driven by grants, not derived by providing online services (computer going down does not impact bottom line). There are few places I can think of that would benefit more by avoiding cloud costs than scientific computing. I'd further say that you're probably over-estimating how valuable mitigating that risk is to anyone, although there are a few limited set of customers that genuinely do care. I'd counter by saying I think you're over-estimating how valuable mitigating that risk is to this crowd. It takes work to figure out which is true. Put like for like in a well managed data center against negotiated and planned cloud services, and the former may still win, but it won't be dramatically cheaper, and figured over depreciable lifetime and including opportunity cost, may cost more. When the closet starts to smoke because they stuffed it with too many cheaply sourced, hot-running cores and GPUs, or gets hacked by one of their postdocs resulting in an institutional HIPAA violation, well, that's not their fault.
Scientists who make this argument almost invariably leave major costs out of their calculation - assuming they can put their servers in a closet,maintain them themselves, do all the security infrastructure, provide redundancy and still get to shared compute when they have an overflow need. But I can also say with confidence that the contest is far closer than they think. Certainly pay as you go, individual project at a time processing will look that way to the scientist.
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Having had the responsibility of providing HPC for a literal buildings full of scientists, I can say that it may be true that you can get computation cheaper with owned hardware, than in a cloud.
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