1.5 exaFLOPS
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Almost 20 years ago, faculty in the chemistry department of Stanford University launched a distributed computing project called Folding@Home (F@H). They sought to understand how proteins self-organize and why this process sometimes goes wrong, causing issues such as cancer and Alzheimer’s Disease.
F@H hit its pinnacle of mindshare—and performance—in 2007, when Sony added it to the PlayStation 3. But like many other projects, it saw a gradual decline in its popularity since. This past March, however, F@H saw a sudden resurgence. Thanks to a confluence of events, notably including the SARS-CoV-2 pandemic, Folding@Home broke the exaFLOP barrier at least one or two years before Intel, AMD, IBM, or Cray could do it.
What does protein folding have to do with COVID-19? The goal is to explore the folds of proteins on the coronavirus’s surface, trying to find spaces for other molecules to fit in a way that can interfere with the virus's function.
The surface of the coronavirus could almost be viewed as a thing of beauty if it weren’t so deadly. It looks something like a Christmas tree ornament, with red appendages that look somewhat like an inverted traffic cone. These are called “spike,” a complex of three proteins. For the virus to attach and infect human cells, spike has to open. Bowman said the function reminded him and his group of the Demogorgon from the show Stranger Things.
Before spike opens, the interface it uses to interact with cells is buried internally; only after it opens can the interface be targeted by drugs. Bowman and his team programmed F@H to hunt for what he called “cryptic pockets” in this interface. “The idea is that if you look at the snapshots of what a protein looks like, it may or may not have pockets amenable to design. We’ve had previous success with antibiotic resistance and Ebola where a small molecule would bind tightly to shut off binding,” he said.
The project is still in the first stage, where researchers look for insight into how the spike proteins function and can be targeted. The project is doing computational screenings of molecules and will prioritize those that bind tightly to the virus’s proteins.
Bowman says he will share his findings with anyone who wants them. “We’re looking to put big data sets on the Internet for others to see how it works or pursue drug design,” he said.
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"Now look here, you Baltic gas passer... " - Mik, 6/14/08
The saying, "Lite is just one damn thing after another," is a gross understatement. The damn things overlap.
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@George-K said in 1.5 exaFLOPS:
@Klaus said in 1.5 exaFLOPS:
I think of this more as a publicity stunt than as a serious research project.
Gotta wonder.
By the way, how's that "SETI at Home" thing working out?
The amount of data they were able to crunch has been incredible. Never, ever would have been able to do that without the screen saver.
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It’s always something.
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@jon-nyc said in 1.5 exaFLOPS:
I once knocked up three women and had triplets in 3 months.
Exactly. Amdahl's law is a good starting point to understand the limitations of parallel computing. It basically says that sequential tasks - like child bearing - cannot be sped up by parallelization. The kinds of problems where the distributed computing architectures like Seti@Home or Fold@Home work at all are called "embarrassingly parallel" problems.
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We did some wonderful things with Mr. Amdahl's machines in the 70s and 80s.
I was working at the Amdahl lab in Sunnyvale when they installed their first parallel processor to exceed a Gigaflop. It was a big secret. There were no signs or identification on the machine so nobody would know what it was. In the couple months I was there it mostly sat idle, at least while we were around it.
We were working next to it on the floor but weren't supposed to know what it was. But one of the Amdahl guys told us. The type of stuff we were doing wouldn't have been able to take advantage of it, at least not much.
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@Copper said in 1.5 exaFLOPS:
I was working at the Amdahl lab in Sunnyvale when they installed their first parallel processor to exceed a Gigaflop.
You mean a single processor with multiple cores? Or do you mean multiple processors?
In any case, I thought that a Cray was the first computer to exceed a Gigaflop. What that a Cray?
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It was an Amdahl machine, it was their (Amdahl's) first machine capable of a Gigaflop. This was early 80s.
And it was not a single processor, it had many CPs. I don't remember exactly how many, my fuzzy recollection is that it was hundreds, not a few or a dozen. I don't remember them competing with anything Cray made.
I believe it used the same air-cooled processors, the 470, that was current in their mainframes at the time. The 470 was the competition for IBM 370 that ruled the world at that time. Air-cooling was a big deal, the IBM mainframes were water cooled and that added to expense and complexity.
