64 cores
256 threads
Running at 1.3 to 1.5 gigahertz with 32 megabytes of cache
Meet the Knights' landing XeonPhi
one of the most insane CPUs in the world
How insane?! (Pretty insane) Well, how does a theoritical 2.5 Teraflops sound?
Got no context for that?
Don't stress!
It's like it's like a lot like
like like look how big this thing is. I could take over the world with this sort of power
But first I need to pay the bills
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[INTRO]
So some background information is in order here as this is no ordinary CPU.
Knights' Landing is the current generation of Xeon Phi Intel's version of what's referred to as a mini core processor
Which is exactly what it sounds like. It's built around the idea of
trading off per thread performance for an obscene number of threads and
maximum throughput. With the theory being that a simpler,
scaled-down core design can dramatically scale up in number while still utilizing existing tools
So we can actually trace Knights' landings lineage back to Project Larrabee first unveiled in mid 2008 as a
GPU
designed around the x86 architecture.
Intel even announced their intent to release a consumer graphics card version of it back in 2010
But since
nobody is talking about dedicated team blue graphics cards today
You should probably realize that that never launched.
So Xeon Phi is what rose from the ashes of that project first appearing in 2012 as a
PCI Express add-in card codenamed "Knights' corner".
And it actually did end up getting used in, what was the world's fastest supercomputer until June 2016.
The newest revision though Knights' Landing looks a little different.
It launched last year unlike Knights corner it works exclusively in the
LGA 3647 socket that high-end Xeon Perley CPUs also slot into.
So adding support for
AVX 512 and its many extensions gives Knights' landing a lot of flexibility in its target market so then
Who's the target market?
I'm glad you asked. Uses for this include Protein Folding Simulation,
Weather Prediction, AI and Neural Network Research Developments and
molecular simulation with libraries like TensorFlow and NAMD being able to take advantage of it
as well as GPU Acceleration.
"Okay then, Linus, so why do you have one?"
I guess because
Super Micro pulled a rookie mistake and sent it to me
I mean obviously all I was gonna do was game on it
And I'm actually kidding about that
At 1.3 gigahertz I can tell you guys right now without firing up a single benchmark what the gaming performance will look like
like that as
as for productivity though
yeah, right out of the gate. It fell flat on its face
coming in at under half of CORE i9 and nearly a third of Threadripper's score in 7-zip and
and Cinebench, CPUMark and RealBench not looking much better.
Even Blender conventionally multi-core friendly benchmark sees
terrible performance given the $1.900 price tag for the chip alone
So know these results won't do it all
Xeon Phi is clearly unlike anything. We've ever tried to benchmark before you'd need like a PhD or something to properly evaluate this thing
Which is where Dr. Kinghorn, our friend over at Puget systems comes in. As a chemist and mathematician
Dr. Kinghorn is no stranger to high-level computation like this and
agreed to remote into our Knights' landing workstation and do some of the testing for us while
also running his own 14 core Xeon 2690 v4 workstation through the same suite to give us a point of comparison.
The results actually pretty surprising in LINPACK, the higher core clock of the traditional Xeon gives it an edge in
Smaller problem sizes, but beyond 5,000 the tables turn dramatically
With the molecular dynamics library NAMD things seem to scale
predictably with the number of atoms being simulated and all the tests wind up being far less favorable to the 0 and 5
the greatest gains in this benchmark actually come from
dedicated compute GPUs.
Though, that is fine for the Xeon Phi these days since it sits in a socket instead of taking up valuable PCIe slots
TensorFlow neural networks bring things back though into the Xeon Phi's wheelhouse, especially in batch sizes larger than 64
So Xeon Phi takes a significant lead over its traditional Xeon cousin
But it should be noted that both of them get creamed by a GPU
further highlighting the importance of large banks of compute GPUs for tasks like these
Though that doesn't mean that Xeon Phi is useless. It's dramatically better performance than a standard Xeon makes it great for
Supplementing GPU compute in workloads like these. Which brings us neatly to the conclusion then
Not quite as good as a GPU for tasks that can be accelerated
far better than a traditional Xeon though in most and
Aaaaand...
finally utterly worthless for just about anything on the Windows desktop
I was actually surprised to see Windows. Even installed we ended up needing a server version of Windows to see all the course
But that is sort of irrelevant
anyway, because this is intended for use in
supercomputers, we're like
MAAASSIVE nodes of these things can all work together to solve complex problems
along with the banks of GPUs that accompany of them.
I mean you're almost
Certainly not gonna be buying anything like this personally any time soon, unless you're like that you like to science for funsies
With that said though you yes, you are very likely to benefit from the work being done using hardware like this and
We're glad we got the opportunity to play with it, it was fun
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