Xeon Phi

Why aren't these used to provide VPSes? (They're 64-core x86 processors in PCIe slots)

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Because they're shit, stop being obsessed with these stupid things.

If it sounds too good to be true, it probably is.

These aren't really necessary or cost effective as a way to setup a bunch of VPS servers.

It's like a group of atom CPUs on a small board.

Can I create 8 virtual PCs and have a battlefield lan party?

Okay then, why are there no GCN ASM VPSes? You can crosscompile C to OpenCL, and a regular GPU can provide thousands of cores.

How do you mean? They're used in supercomputers, which leads me to think that they're price efficient.

For doing a bunch of calculations over time it's good, for hosting a VPS it's not the best task to be suited for.

Also hosting a VPS with everything offloaded to the GPU is possible but it can't be the most efficient way to do that or else companies would already do it.

Because probably nobody wants to pay for an emulated core on a GPU.

originel donut steal

>beating AMD

Fuck forgot to change it to intel

oh well :^)

>implying AMD isn't their own worst enemy

this would be great for cracking, but way too fucking expensive.. holy shit.

You get tiny amount of ram per thread.

But it's not emulated, it's cross-compiled
(x86 asm / C / C++ / whatever) -> LLVM -> OpenCL -> GCN ASM
No, why would it be better than GPU? oclHashcat exists, and I can get 10 R9 290 for the price for one of those.
>... up to 72Airmont(Atom) cores with four threads per core, ... supporting for up to 384GB of "far" DDR4 RAM
But good point, that's why the GPU idea wouldn't work. Or can GCN ASM code use PCIe as GPIO on pin level?

i'm saying it's too expensive. so it wouldn't be good compared to GPUs you can get at regular retailers can you read or what?

>You can crosscompile C to OpenCL
and it's going to very slow
besides, i think what you meant is transpiling, i. e. turning source code in 1 language into source code of another language. transpiling is generally a mess and some features are terribly implemented(because things that are easy in C might not be easy in OpenCL) or not available at all.
low RAM+bandwidth(to RAM)

Mozilla is turning C into rust now, how bout that?

>Or can GCN ASM code use PCIe as GPIO on pin level?
i highly doubt that. You don't need that to access (main) RAM from PCIe devices though. But latency will be shit. CPUs have massive caches for a reason. I also suspect that PCIe throughput is lower than RAM throughput.
please specify what you mean by "turning C into Rust" or provide a source.

I actually got a chance to use one of these. They're pretty odd, they are completely independent Linux computers with lots of cores running inside your computer. You can even ssh into it through a virtual network connection and send it compiled code to execute on it's many many cores.

If they can do that (and they should) the pcie spec flies out the window. The ram would be accessed using the DDR spec, with the remaining pins going to pcie as usual
C to Rust is much easier.
Yeah, transpiling. ansmart.co.uk/?q=node/54 seems to be quite fast.

Precisely. You just install a xen kernel and rent the instances out.

I'm curious by "lots" you mean like 20 cores per computer?

So what talks over PCI-e then?
Anything high bandwidth?

>transpiling seems to be quite fast
that depends a lot on the language
>If they can do that (and they should)
no, they shouldn't. The CPU load/store units that handle memory transfers can't even access the RAM directly, they can only ask the L1 cache, which in turn might ask the L2 cache etc. until it goes out to RAM. High-speed interconnects are extremely difficult to build and develop, and what actually goes over the wire is rather sophisticated. This is all implemented in hardware in specialized silicon doing PCIe encoding/decoding, error correction, etc.
Meanwhile the GCN/Xeon Phi/whatever cores don't care(or know) about all the crap PCIe has to do to actually transmit stuff.
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waht do you mean by "talks over PCIe"?
look it up, xeon phi had ~60 cores at some point

>waht do you mean by "talks over PCIe"?
Why have it plugged in over PCI-e when it could just be plugged in over ethernet?

ssh doesn't talk ethernet, it talks TCP/IP(which can be run over MPLS, 2G, 3G, LTE, DSL, DOCSIS and a lot of other physical connections, not necessarily ethernet.)

What I'm asking is, what benefit does the thing have being plugged directly to a computers motherboard rather than just being a completely independent device sitting on the network, like a raspberry pi on steroids?

higher throughput and latency
>High-speed interconnects are extremely difficult to build and develop
and incredibly dependant on length.
the longer an electrical connection is the more interference you get, which limits speed.
Probably the best example of this is DSL, the speed of which depends on how much copper wire there is between your home and your internet provider's infrastructure. It doesn't matter what you hook up to the wires, you won't get much higher than whatever DSL achieves if they're a few 100 meters long.

No, youd have to know how.

>b-but supercomputers
fucking stupid redditor

>supercomputers
>cost effective
pick one

245 fucking watts, that's why

>Why aren't these used to provide VPSes? (They're 64-core x86 processors in PCIe slots)

Because what market would they serve? And how would that market benefit from it?

Xeonphi cards, themselves, exist in a odd middle-ground. They're not BIG N STRONK like traditional X86 Server Processing, capable of doing complex calculations per core very quickly. And they're not as massively parallel as a GPGPU solution, with it's 4000+ "cores" (more like threads, really) so they can't run as many simple instructions at the same time. The Xeonphi's individual cores can do more than any of the individual GPU "cores" can, but it has so fewer of them, if a program is optimized to just split complex maths down into more basic maths, and feed MANY, MANY, MANY more times of these maths into the GPGPU, there is no reason for it not to finish faster than the Xeonphi could. Or if a program is optimized to condense these maths into complex algorithms, the STRONK traditional processors can muscle them out a lot faster than the little Phi's could.

They're used in SuperComputing because they're a lazy solution that require minimal re-working of programs to get them compatible. Reworking for GPGPU takes a lot of time, energy, and effort. You can't just toss code through a transcompiler and expect good results. Code is best built and optimized for the architecture it's going to run on. But if you have an existing x86 compatible program that runs on your distributed processing network anyway, and the bottleneck is number of threads vs the capabilities of the threads, then XeonPhi is a "cheaper" solution than reworking that program.