$4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research
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Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research
#2Man, and I thought it was bad when I set in motion a 3 hour computation and lose it due to a bug in the code that writes the results to disk. At least it doesn't set me back $15k to redo the computation...
Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research
#3> As impressive as it sounds, such a cluster can be spun up by anyone with the proper expertise, without talking to a single employee of Amazon.
This isn't actually true. There's initially an instance limit of 20, and you have to contact Amazon to get it lifted. You could probably order just as many servers at Softlayer or purchase them at Dell without talking to anyone (except the guy who confirms your credit card).
After all, they're not going to let anyone run up a $3 million bill on the hope that it'll be paid at the end of the month!
Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research
#4$4,829 per hour isn't the most impressive metric here. It ran for only 3 hours, at a total cost of $14,486 - compared to the build cost and lead time involved in building a "$20-25m data center".
This has huge implications for the availability of supercomputers for smaller organizations and use cases.
Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research
#5Stowe was just speaking at AWS summit, lots of AWS goodness there: http://aws.amazon.com/live/
Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research
#6The cluster used a mix of 10 Gigabit Ethernet and 1 Gigabit Ethernet interconnects. However, the workload was what’s often known as "embarrassingly parallel," meaning that the calculations are independent of each other. As such, the speed of the interconnect didn’t really matter.
Ah, if only this were true for everything. It'd make everyone's lives a lot easier. :-) Unfortunately there are a lot of applications out there where inter-node communication is incredibly important: computational fluid dynamics, in all its varied forms, is a good example of a latency-bound application. This covers weather forecasting, aerodynamics, dynamic mechanical modeling, and so on.
What I find interesting is that to get to 51,000 cores, they had to use AWS datacenters all over the world. I'd love to know what kind of resources are actually available in any given datacenter. It will vary at any given time, but it would be useful to know how many cores are "close" to each other in a networking sense, for applications were latency matters.
Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research
#7And yet, no results from their massive computation. Schrodinger is well known for being a company of liars and frauds, and unfriendly to open source and other ideals of our community.
Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research
#8Two things struck me about that article, the pharmaceutical guy who felt like with enough cores they could find the cure to cancer, and Cycle's challenge of moving past 50,000 cores.
What struck me is that I wonder why Google (or Amazon) hasn't put out the cure for cancer. The actual extent of Google's infrastructure is classified, but using open sources its clear that putting together even half a million 'cores' is not a huge project for them. (Think of it this way, they spent a billion dollars building a data center that the actual building/land/etc estimates out at about 200M.)
Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research
#9While it's nice from a technical perspective, this is unlikely to lead to a cancer cure. Having worked in cancer drug development, I can tell you, there is no shortage of cancer targets. Researchers have a list of targets they want to hit, and chemists are pretty darn good at designing small molecule compounds to hit them.
The problem in cancer is not that we don't understand individual proteins or the way that drugs bind to them (the problem being solved in this article). It is that the biology of cancer is a crazy web of highly complex interactions and feedback loops of which we have a pathetically rudimentary understanding. So even when you think you're hitting a target that should kill the cancer, you find out there's some side pathway that spools up and limits the drug's efficacy (or worse, the cancer cells actively pump your compound out). If I recall, something like >95% of new cancer therapies fail in clinical trials. Most of the failure in this drug category is due to lack of efficacy (even though they hit a target, they don't do jack for treating the cancer). If you could make that number 85%, you'd probably be a Nobel contender.
Unfortunately, there's no digital route here. What needs to be done is a lot of slow, messy "wet bench" biology. There is no electronic shortcut to understanding how living cells work.
Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research
#10While it's nice from a technical perspective, this is unlikely to lead to a cancer cure. Having worked in cancer drug development, I can tell you, there is no shortage of cancer targets. Researchers have a list of targets they want to hit, and chemists are pretty darn good at designing small molecule compounds to hit them. The problem in cancer is not that we don't understand individual proteins or the way that drugs…
I agree mostly with your post but there are computational approaches being developed that may help improve our understanding of these cancer networks.
They will in no way eliminates or reduce the need for wet lab biology but hopefully it will couple with improvements in high throughput experimental technology to help us design and make sense of experiments targeted at understanding the whole phenomena.