64 cores
256 threads running at 1.3 to 1.5 gigahertz with 32
megabytes of cash meet
the knights landing zeon phi one of the most insane cpus in the world
how insane well how does a theoretical two and a
half teraflop 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 can take over the world with this sort
of power but first i need to pay the bills which
is why today's video is brought to you by tunnelbear tunnelware makes it easy
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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 knight's landings lineage back to project larabee
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 codename knight's corner
and it actually did end up getting used in what was the world's fastest
supercomputer until june 2016. the
newest revision though knight's landing looks a little different it launched
last year and unlike knight's corner it works exclusively in the lga 3647 socket
that high-end xeon pearly cpus also slot
into so adding support for avx-512 and
its many extensions gives knight's 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 and development and molecular simulation with libraries like
tensorflow and the uiuc's namd being
able to take advantage of it as well as
GPU acceleration okay then Linus
so why do you have one
um 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 for productivity though yeah right out of the gate it falls flat
on its face coming in at under half of
core i9s and nearly a third of threadripper's score in 7-zip and
cinebench CPU mark and real bench not looking much better even blender a
conventionally multi-core friendly benchmark sees terrible performance
given the 1900 price tag for the chip alone
so no 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 night's 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 5000
the tables turn dramatically with the molecular dynamics library and
AMD things seem to scale predictably
with the number of atoms being simulated and all the tests wind up being far less
favorable to the xeon phi the greatest gains in this benchmark
actually come from dedicated compute gpus
though that is fine for the phi these days
since it sits in a socket now 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 its 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 finally utterly worthless for just about anything on the Windows desktop i
was actually surprised to see Windows even install we ended up needing a
server version of Windows to see all the cores but that is sort of irrelevant
anyway because this is intended for use in super computers where like
massive nodes of these things can all work
together to solve complex problems along with the banks of gpus that accompany
them i mean you're almost certainly not going to be buying anything like this
personally anytime soon unless you're like a 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 speaking of things that are fun
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