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AWS doesn't make sense for scientific computing

noahlebovic.com

221–230 of 281 posts

Re: AWS doesn't make sense for scientific computing

#221

Earlier quoted context omitted.

That is not a law.

There are actually laws around such things. You can read about them here: https://www.hhs.gov/ohrp/index.html

That only applies to government / government sponsored research. That is different from someone doing their own research

Re: AWS doesn't make sense for scientific computing

#222

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. Certainly pay as you go, individual project at a time processing will look that way to the scientist. But I can also say with confidence that the contest is far closer than they think. Scientists who make this argument almos…

They leave out major costs because they don't pay those costs. Power, Cooling, Real Estate are all significant drivers of AWS costs. Researchers don't pay those costs directly. The university does, sure, but to the researcher, that means those costs are pre-paid. Going to AWS means you're essentially paying for those costs twice. plus all the profit margin and availability that AWS provides that you also don't need.

Definitely some truth in this, and the way research funding is managed, especially with Federal grants, makes it incredibly difficult to sort out and identify the right solution.

Re: AWS doesn't make sense for scientific computing

#224

Earlier quoted context omitted.

There are actually laws around such things. You can read about them here: https://www.hhs.gov/ohrp/index.html

That only applies to government / government sponsored research. That is different from someone doing their own research

This is true, but to say it is "not a law", as you did, completely unqualified, is incorrect. If the research project is connected with a government grant (and many are) you need to pay attention to those laws. Many universities also have their own policies you need to follow, regardless. (Requiring informed consent and protecting people's privacy seems like a good thing.)

Re: AWS doesn't make sense for scientific computing

#225

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. Certainly pay as you go, individual project at a time processing will look that way to the scientist. But I can also say with confidence that the contest is far closer than they think. Scientists who make this argument almos…

I'd much rather store HIPAA data on a server in my office or closet than worry I got all the IAM settings right. And if I fire someone, security makes sure they can't get in the building. You cannot say the same about the cloud. Yes, I know you can do cloud security right, but on prem security is just harder to mess up.

More than half of security penetrations in our institution (A medical center - research - med school complex) over the 8 years I worked there, ending in 2020, came through the research arm, even though Research accounted for no more than 10% of enabled servers in the infrastructure. And we're talking APT penetrations. They weren't looking for HIPAA data (although I used that example in my original post), they were looking for a path to permanent presence in our network in order to mine research. So, why did they come through Research? Because a PI buys some equipment - servers or other network enabled stuff - puts a grad student or post doc in charge of it, and enjoys his or her cheap compute. But that student or post doc is not an infrastructure expert, and most definitely doesn't understand enterprise security. Next thing you know, we've got an APT owned server on the inside of the network. (And none of that is counting the ones where the post doc is a foreign national who actually intends to use their position to compromise their employer. Had that happen too.) There are a some computational scientists who actually do understand this stuff, but they're rare. Being on the cloud does not inherently fix this oroblem, but to fix it you have to be on institutionally, professionally managed infrastructure, and once you are, the cost differential between owned infrastructure and well negotiated, managed cloud infrastructure becomes much more nuanced.

Re: AWS doesn't make sense for scientific computing

#226

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. Certainly pay as you go, individual project at a time processing will look that way to the scientist. But I can also say with confidence that the contest is far closer than they think. Scientists who make this argument almos…

Is a postdoc hacking a cluster something you have seen before? I am genuinely curious because I worked on a cluster owned by my university as an undergrad and everyone was kind of assumed to be trusted. If you had shell access on the main node you could run any job you wanted on the cluster. You could enhance security I just wonder about this threat model, that's an interesting one. I am sure it happens to be clear.

Yes. Probably not surprise that the postdoc was a PRC national. Very competent in their field of study, but also in this country with instructions from an APT group.

Re: AWS doesn't make sense for scientific computing

#227
post #85

I've never worked in this space, but I'm curious about the need for massive egress. What's driving the need to bring all that data back to the institution? Could whatever actions have to be performed on the data also be performed in AWS? Also while briefly looking into this I found that AWS has an egress waiver for researchers and educational instiutions: https://aws.amazon.com/blogs/publicsector/data-egress-waiver..…

I've worked the last few years in a research institute well-funded by academic standards. During that time, people around me have used self-hosted hardware, at least three different cloud providers, and HPC clusters hosted by several different organizations. I've also worked with people from many other institutions, each of which has made its own infrastructure choices.

You may use AWS yourself, but your collaborators have made their own choices for their own reasons. The data goes where it's needed, often crossing institutional boundaries.

Re: AWS doesn't make sense for scientific computing

#228
post #220

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. Certainly pay as you go, individual project at a time processing will look that way to the scientist. But I can also say with confidence that the contest is far closer than they think. Scientists who make this argument almos…

Perspective from a computational biologist: Campus hosted HPC means the direct cost pressure is seen as IT staff and hardware related costs. Researchers are encouraged to use the available capacity. This is good. Externally-hosted HPC means every single compute job is seen as something that directly costs money. This negatively affects the quality of scientific output (research playfulness / creativity / focus on the…

Yes. The costing models that are used (and often required by granting agencies) make apples to apples cost comparisons almost impossible, and impose undoubted and significant false costs on research budgets. No question this is true.

Re: AWS doesn't make sense for scientific computing

#229
post #32

Earlier quoted context omitted.

Let me echo this as someone who once was responsible for HPC computing in a research intensive public university. Most career academics have NO IDEA how much enterprise computing infrastructure costs. If a 1 terabyte USB hard drive is $40 at Costco we (university IT) must be getting a much better deal than that. Take this argument and apply it to any aspect of HPC computing and that's what you're fighting against. Th…

I remember the first time a server caught fire in the closet we kept the rack in. Backups were kept on a server right below the one on fire. But, y'know, we saved money.

I never saw an actual fire, but I we did see smoke, in a closet, on a floor that was 90% patient care, but happened to have a research area as well because the research needed access to expensive radiography equipment. The close was literally stuffed with what amounted to gaming machines, purchased with grant money through an importer, directly from China. The guy who set them up was smart enough to put them all behind a little firewall, so the enterprise network couldn't see them. It was a (literally) hot mess, both infrastructure and security-wise.

Re: AWS doesn't make sense for scientific computing

#230

I think this post is identifying scientific computing with simulation studies and legacy workflows, to a fault. Scientific computing includes those things, but it also includes interactive analysis of very large datasets as well as workflows designed around cloud computing. Interactive analysis of large datasets (e.g. genome & exome sequencing studies with 100s of 1000s of samples) is well suited to low-latency, serv…

I've followed Hail and applaud the Broad Institute's work wrt establishing better bioinformatics software and toolkits so I hope this doesn't come as rude, but I can't imagine an instance in a real industry or academic workflow where you need 300ms feedback from an experiment to "maintain flow" considering how long experiments on data that large (especially exome sequencing!) take overall? My (likely lacking) imagina…

300ms is my ideal latency, but we don’t achieve that under all circumstances. Even for blob storage, I see as much as 100ms latency. That said, my laptop has maybe 8 cores. Even if I had 0ms reads from an SSD, I’m compute bound for some tasks.

Moreover, I think we have differing definitions of “experiment”. In the context of a sequencing study, I think an “experiment” can be as simple as answering the hypothesis: does the missingness of a genotype correlate with any sample metadata (e.g. sequencing platform). You might try to test that hypothesis by looking at a PC1-PC2 plot with points colored by sequencing platform where the PCA is conducted on the 0/1 indicator matrix of missingness.

In the dry lab, that is what I mean by experiment. By that definition, a scientist does many experiments a day. Particularly for sequencing studies, these experiments are data-intensive, I need to run a simple computation on a lot of data to confirm the hypothesis.

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