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64 cores

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256 threads running at 1.3 to 1.5 gigahertz with 32

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megabytes of cash meet

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the knights landing zeon phi one of the most insane cpus in the world

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how insane well how does a theoretical two and a

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half teraflop sound got no context for that

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don't stress it's like it's like a lot like

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like like look how big this thing is i can take over the world with this sort

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of power but first i need to pay the bills which

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so some background information is in order here as this is no ordinary CPU

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knights landing is the current generation of xeon phi Intel's version

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of what's referred to as a mini core processor which is exactly what it

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sounds like it's built around the idea

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of trading off per thread performance

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for an obscene number of threads and maximum throughput

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with the theory being that a simpler scaled down core design can dramatically

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scale up in number while still utilizing existing tools

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so we can actually trace knight's landings lineage back to project larabee

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first unveiled in mid 2008 as a GPU

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designed around the x86 architecture Intel even announced their intent to

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release a consumer graphics card version of it back in 2010

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but since nobody is talking about dedicated team

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blue graphics cards today you should probably realize that that

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never launched so xeon phi is what rose

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from the ashes of that project first appearing in 2012 as a pci express

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add-in card codename knight's corner

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and it actually did end up getting used in what was the world's fastest

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supercomputer until june 2016. the

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newest revision though knight's landing looks a little different it launched

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last year and unlike knight's corner it works exclusively in the lga 3647 socket

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that high-end xeon pearly cpus also slot

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into so adding support for avx-512 and

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its many extensions gives knight's landing a lot of flexibility in its

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target market so then who's the target market i'm glad you

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asked uses for this include protein folding simulation

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weather prediction ai and neural network

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research and development and molecular simulation with libraries like

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tensorflow and the uiuc's namd being

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able to take advantage of it as well as

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GPU acceleration okay then Linus

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so why do you have one

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um i guess because super micro pulled a rookie mistake and

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sent it to me i mean obviously all i was gonna do was game on it and i'm actually

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kidding about that at 1.3 gigahertz i can tell you guys

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right now without firing up a single benchmark what the gaming performance

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will look like like that

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as for productivity though yeah right out of the gate it falls flat

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on its face coming in at under half of

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core i9s and nearly a third of threadripper's score in 7-zip and

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cinebench CPU mark and real bench not looking much better even blender a

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conventionally multi-core friendly benchmark sees terrible performance

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given the 1900 price tag for the chip alone

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so no these results won't do it all

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xeon phi is clearly unlike anything we've ever tried to benchmark before

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you'd need like a phd or something to properly evaluate this thing

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which is where dr kinghorn our friend over at puget systems comes in as a

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chemist and mathematician dr kinghorn is no stranger to high-level computation

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like this and agreed to remote into our night's landing workstation and do some

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of the testing for us while also running his own 14 core xeon 2690 v4 workstation

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through the same suite to give us a point of comparison the results

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actually pretty surprising in linpack the higher core clock of the

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traditional xeon gives it an edge in smaller problem sizes but beyond 5000

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the tables turn dramatically with the molecular dynamics library and

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AMD things seem to scale predictably

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with the number of atoms being simulated and all the tests wind up being far less

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favorable to the xeon phi the greatest gains in this benchmark

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actually come from dedicated compute gpus

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though that is fine for the phi these days

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since it sits in a socket now instead of taking up valuable PCIe slots

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tensorflow neural networks bring things back though into the xeon phi's

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wheelhouse especially in batch sizes larger than 64.

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so xeon phi takes a significant lead over its traditional xeon cousin

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but it should be noted that both of them get creamed by a GPU

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further highlighting the importance of large banks of compute gpus for tasks

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like these though that doesn't mean that xeon phi

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is useless its dramatically better performance than a standard xeon makes

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it great for supplementing GPU compute in workloads

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like these which brings us neatly to the conclusion then

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not quite as good as a GPU for tasks that can be accelerated

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far better than a traditional xeon though in most

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and finally utterly worthless for just about anything on the Windows desktop i

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was actually surprised to see Windows even install we ended up needing a

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server version of Windows to see all the cores but that is sort of irrelevant

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anyway because this is intended for use in super computers where like

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massive nodes of these things can all work

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together to solve complex problems along with the banks of gpus that accompany

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them i mean you're almost certainly not going to be buying anything like this

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personally anytime soon unless you're like a you like to science for funsies

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with that said though you yes you are very likely to benefit from the work

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being done using hardware like this and we're glad we got the opportunity to

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play with it it was fun speaking of things that are fun

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dislike this video you can hit that button but if you liked it hit like get

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if you like work at a university or something

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it's like i'll know that's what happened if like you know 2 000 xeon 5's show up

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on like our amazon report or whatever anyway the point is also in the

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