- looks similar to P100 (interposer with HBM)
- 55 teraops/s performance
- custom number format (variable length fixed point?)
- simplified memory architecture (no cache?)
- no info about power consumption
No automatic cache hierarchy. There is local memory, which you manage explicitly. More info here:
Ha, ha. Yeah… no. For one thing, there's no mention of its power consumption, no CUDA support, questionable memory design (sure, you can get a million TFlops without cache, now try to get that chip to do anything useful), etc.
Intel probably bought 'em to work on integrated GPUs or Xeon Phi or something.
Ha, ha. Yeah… no.
> there's no mention of its power consumption
Can't be tremendously higher than Pascal for reasons of physics.
> sure, you can get a million TFlops without cache, now try to get that chip to do anything useful
"Without cache" is certainly an exaggeration. It won't have a globally coherent cache hierarchy in the style of CPUs. It certainly will have various on chip memories to hold intermediate results. Neural net workloads are incredibly predictable and homogeneous and are essentially the perfect scenario for hand optimization of data flows to beat automatic caching.
> no CUDA support
You're just being silly now. CUDA isn't a standard, it's proprietary to NVIDIA and this isn't a general purpose processor anyway.
I would love to agree with you but the reality is that CUDA is the de-facto industry standard e.g. .
> and this isn't a general purpose processor anyway.
The "GP" part in GPGPU would like to disagree... 
Case in point, GPUs are standard (for now) for training DNNs, but the big server farms that actually do the scoring run on Xeons.
However, Intel dominance is not to be underestimated, they definitely can make industry wide impact quickly. Just saying you can not easily draw parallels here
Personal attacks are not OK on Hacker News. Please leave these out of comments.
If Intel can ape Nvidia at deep learning then it is a big growth opportunity for them.
I really don't think CUDA support is important for nervana's offering. They think of themselves as the Apples of deep learning - they want to offer an integrated stack from the chip all the way to the APIs. The way most people use deep learning you don't really need to know CUDA, you just need to use a library that is fast. So it's enough that nervana's engineers know how to write deep learning libs for their own chip. Furthermore I can't see Intel caring that much about CUDA support, since CUDA is owned by Nvidia.
What I've heard about the chip makes it sound really exciting. Many of the trade-offs in deep learning are different from the ones you do in graphics, so specialized hardware makes sense.
As good as this could be, it would be even better if we also get an open-source software stack that can compete with Nvidia's proprietary CUDA stack, which currently dominates everywhere (except maybe in Google's data centers).
You've already got that. It's called OpenCL.
https://en.wikipedia.org/wiki/Comparison_of_deep_learning_so... (see column "Open CL support")
Like it or not, Nvidia's currently cornered the market. With their outstanding work on CUDNN et al, they are milking that cow for all it's worth.
Also lets Nervana scale and potentially get their Neon deep learning framework out there in the face of bigger players (a la TensorFlow).
All in all it's good to see the competition in this space.
I figured Intel was down and out in Santa Clara without a strong deep learning play
That all changed today.
Intel has been bouncing all over the place trying to break into deep learning. If they don't screw this up, they just found their way in IMO.
Why? Is there a competitor that has leveraged a more modern process technology?
However, getting access to Intel's fabs makes them a lot more interesting and competitive. It's not a slamdunk for Intel yet because they still have to incorporate this into their product line (anyone seen Altera's Stratix 10 yet? Because that was supposed to be 2014's 10+ TFLOP GPU killer), but it's a fantastic acquisition and I wish them the best.
My assumption, is that Intel will lease the chips + software, similar to the way HP, Dell, etc. Lease GPU machines.
Nervana honestly woukd have been obsolete and dead pretty soon without this. I see this as an acuire-hire.
For $350 million is not an acquire-hire.
Update: An earlier version of the story indicated the purchase price was more than $350 million, according to a source. Multiple investors told Recode the purchase price was significantly above that price, with one pegging it at $408 million.