Slashdot Mirror
Intel Launches 72-Core Knight's Landing Xeon Phi Supercomputer Chip (hothardware.com)
MojoKid writes: Intel announced a new version of their Xeon Phi line-up today, otherwise known as Knight's Landing. Whatever you want to call it, the pre-production chip is a 72-core coprocessor solution manufactured on a 14nm process with 3D Tri-Gate transistors. The family of coprocessors is built around Intel's MIC (Many Integrated Core) architecture which itself is part of a larger PCI-E add-in card solution for supercomputing applications. Knight's Landing succeeds the current version of Xeon Phi, codenamed Knight's Corner, which has up to 61 cores. The new Knight's Landing chip ups the ante with double-precision performance exceeding 3 teraflops and over 8 teraflops of single-precision performance. It also has 16GB of on-package MCDRAM memory, which Intel says is five times more power efficient as GDDR5 and three times as dense.
So, somewhere someone at AMD is going "fuck it, we're going to 128 cores".
Damn ... that's a crap pile of cores ... that's like, Skynet in a box or something.
The mind reels.
Lost at C:>. Found at C.
It is probably a good chip for it's niche, so you would think they would have less bloviation in their intro video. If this was anyone else I would assume they were mostly trying to fleece more investors before they inevitably went belly up. It's so bad that major league sports style animation with yelling pitchman and a pounding beat would be an improvement. That bad.
Why is Snark Required?
Guess I read it wrong. FirePro S9170 produces 2.6Tflops.
That chip is a Beowulf cluster.
If it weren't for deadlines, nothing would be late.
I've been asleep for 20 years so I guess CISC won?
Zoid.com
Defects in the process bleeding edge process are the main reason to use the older process. When they make one of these insane multi-core parts the die size is very large (sometimes taking up a whole 26 by 32mm scanner field) thus the yields are hit harder by defects. On a more consumer level chip they may have 4 or more die in a scanner field. A single defect in this field will take out one of the four die resulting a a yield of 75% for that field. However in the case of a single die for the whole field the yield would be zero with the exact same number of defects per mm^2. I am sure they have a greater understanding of where their defects come from on the older 22nm process these days and can ensure good yields even with a huge die size.
An additional reason they would use the older process is a chip of this level of complexity probably requires tighter overlay and critical dimension (CD) control than the "standard" 22nm process to work well. Having a well defined process makes tuning all of these factors much easier and it also helps decouple if it was it the process or possibly a issue in the design when initial silicon runs do not work exactly as intended.
This has been corrected in the post. Intel is in fact using their 14nm node for Knights Landing.
I think the real question is FLOP/Watt. I really don't know how the two will stack up. Might also depend on whether or not the stream processors in nvidia gpus are better suited to the workload than x86 cores?
raytrace version of wolfenstein, pretty much.
cost effectivity for other uses.. well..
world was created 5 seconds before this post as it is.
Bitcoin mining, of course -- it may not be as fast as a similarly-priced GPU farm, but the coins it creates will be of the highest possible quality and workmanship.
I don't care if it's 90,000 hectares. That lake was not my doing.
Bah, turn on Flash and IE and it'll be 2 minutes and glowing white. ;-)
Lost at C:>. Found at C.
While supercomputing is a very small section of the computing world, it's not that hard to understand.
First of all, this would make for a terrible graphics card. This (deliberately) sits between a CPU and GPU. Each core in a Phi has more branching support, memory space, more complex instructions, etc than a GPU core, but is still more limited than a Xeon core (but it has wider SIMD paths).
A GPU has many more cores that have a much more limited set of operations, which is what is needed for rapid graphics render. But, those limited sets of operations can also very useful in scientific computing.
I haven't seen anybody try a three pronged approach (CPU/Phi/Nvidia Tesla), but I will admit I didn't look very hard. This is all in the name of solving really big problems.
That is what happens when u use Windows.
A meta-beowulf.
So what exactly is the real world application of such a beast?
All of the things where you really, really wish that you could do GPU offloading, but can't because you have diverging flow control and the GPU version ends up coming nowhere near to the theoretical peak performance of the hardware. The Xeon Phi cores are pretty simple, but there are loads of them, they have real branch prediction and caches (so handle the same kind of workloads as normal CPU cores, just a bit slower) and have fairly beefy vector units (so when they're running in a straight line they're actually pretty fast). Anything that you can make run on multiple threads should work nicely on them. That includes a load of HPC code that uses OpenMP, but which doesn't map particularly well to a CPU programming model without significant rewriting and redesigning of the core algorithms.
I am TheRaven on Soylent News
Have you tried having nine wives?
Society is getting to the point where technology is literally climbing up our asses,
So you are saying that "big money" has next generation butt plugs?
APK likes to ask for responses to the same things over and over. Maybe he just likes the responses?