AMD Radeon VII: High-End 7nm Vega Video Card
anandtech.com
AMD Radeon VII: High-End 7nm Vega Video Card
1–10 of 91 posts
Re: AMD Radeon VII: High-End 7nm Vega Video Card
#2Its an interesting design for sure.
4x Stacks of HBM2 means 1TBps memory bandwidth at 16GB. Only 60-compute units enabled (maybe 4-CUs are expected to break during manufacturing? Its a weird number for sure...).
Since it shares dies with the MI50, the Radeon VII will have 1/2 speed double-precision, making this the cheapest high-performance double-precision card in existance.
------
FP16 compute is supported at double speed, but there are no tensor cores. So FP16 matrix multiplication / tensor ops are still a major benefit to NVidia.
But the memory size and bandwidth is quite salivating. That's a lot of bandwidth, and a number of problems are known to be memory-bound. Deep learning enthusiasts probably will stick to NVidia cards, but other compute problems may want to start playing around with this thing.
------
Video gamers seem meh about the specs. But I think anyone looking at this card for its compute performance would be impressed.
Re: AMD Radeon VII: High-End 7nm Vega Video Card
#3Its an interesting design for sure. 4x Stacks of HBM2 means 1TBps memory bandwidth at 16GB. Only 60-compute units enabled (maybe 4-CUs are expected to break during manufacturing? Its a weird number for sure...). Since it shares dies with the MI50, the Radeon VII will have 1/2 speed double-precision, making this the cheapest high-performance double-precision card in existance. ------ FP16 compute is supported at doubl…
Perfect dies (64 CUs) get sold as a Radeon Instinct MI60 at a much higher price.
Re: AMD Radeon VII: High-End 7nm Vega Video Card
#4Its an interesting design for sure. 4x Stacks of HBM2 means 1TBps memory bandwidth at 16GB. Only 60-compute units enabled (maybe 4-CUs are expected to break during manufacturing? Its a weird number for sure...). Since it shares dies with the MI50, the Radeon VII will have 1/2 speed double-precision, making this the cheapest high-performance double-precision card in existance. ------ FP16 compute is supported at doubl…
Perfect dies (64 CUs) get sold as a Radeon Instinct MI60 at a much higher price.
Good point, and that makes a lot of sense.
Re: AMD Radeon VII: High-End 7nm Vega Video Card
#5> They are presumably not going to be able to match NVIDIA’s energy efficiency, and they won’t have feature parity since AMD doesn’t (yet) have its own DirectX Raytracing (DXR) implementation.
I assume this means that it won't support raytracing at all? Or will it, but with some non-DXR implementation?
Re: AMD Radeon VII: High-End 7nm Vega Video Card
#6> They are presumably not going to be able to match NVIDIA’s energy efficiency, and they won’t have feature parity since AMD doesn’t (yet) have its own DirectX Raytracing (DXR) implementation. I assume this means that it won't support raytracing at all? Or will it, but with some non-DXR implementation?
They might support it with a software upgrade in the future, but I doubt it.
Re: AMD Radeon VII: High-End 7nm Vega Video Card
#7> They are presumably not going to be able to match NVIDIA’s energy efficiency, and they won’t have feature parity since AMD doesn’t (yet) have its own DirectX Raytracing (DXR) implementation. I assume this means that it won't support raytracing at all? Or will it, but with some non-DXR implementation?
NVidia's raytracing is hardware accelerated. There's specific cores that can ONLY traverse a BVH tree built into the NVidia hardware. Furthermore, NVidia's raytracing features leverage FP16 matrix multiplication for denoising.
The Radeon VII will certainly be slower at raytracing (if AMD ever decides to support the feature). It has FP16 support and huge RAM bandwidth (which will help traverse a BVH Tree), but I would expect it to be many times slower than dedicated hardware units. Without tensor cores (VII only supports hardware-accelerated FP16 Dot-products), there's no way it'd keep up with Nvidia on denoising or BVH traversals.
Re: AMD Radeon VII: High-End 7nm Vega Video Card
#8> They are presumably not going to be able to match NVIDIA’s energy efficiency, and they won’t have feature parity since AMD doesn’t (yet) have its own DirectX Raytracing (DXR) implementation. I assume this means that it won't support raytracing at all? Or will it, but with some non-DXR implementation?
It likely won’t without ray tracing specific hardware. Theoretically, they don’t need the hardware and can use the directx ray tracing api and do software acceleration. It will just run very very slowly.
https://www.anandtech.com/show/12547/expanding-directx-12-mi...
Re: AMD Radeon VII: High-End 7nm Vega Video Card
#9In July 2015 AMD released a 28nm chip with more GCN compute units than this card at a lower price - the Radeon R9 Fury X had the full 64 CUs / 4096 shaders enabled for $649. And it was considered a bit of a dud as a product. This Radeon VII is 2.5 process nodes better, but launches with 60 CUs / 3840 shaders enabled. All still on essentially the GCN architecture. And it launches at $699, more than three and a half years after the former.
Yet due to sheer clock speed increases and HBM improvements (16GB, 1 TB/s, wow) they actually seem surpisingly competitive. I'm both incredibly impressed and incredibly underwhelmed.
Re: AMD Radeon VII: High-End 7nm Vega Video Card
#10Its an interesting design for sure. 4x Stacks of HBM2 means 1TBps memory bandwidth at 16GB. Only 60-compute units enabled (maybe 4-CUs are expected to break during manufacturing? Its a weird number for sure...). Since it shares dies with the MI50, the Radeon VII will have 1/2 speed double-precision, making this the cheapest high-performance double-precision card in existance. ------ FP16 compute is supported at doubl…
> Deep learning enthusiasts probably will stick to NVIDIA cards
We've been building the wrong hardware for ML for a while now.
A TPU doesn't delivery supremacy for problems over GPU hardware. It's a Google senior engineering retention and PR project.
Exceedingly few problems resemble image recognition. You wouldn't be able to tell from the research, because due to the tools it's sort of the only affordable thing to do.
Playing Go barely looks like it. Or more accurately, Go doesn't look like most other games. Molecular physics and synthesis barely looks like it. Neural programs/neural Turing machines that matter (converting complex sim code like game rules and physics into neural networks via learning) may never achieve the accuracy or performance/watt necessary to really compete with just making a bunch of CPUs or straight up dedicated hardware.
Word embeddings are a disaster. People keep trying to do innovative stuff with it, and it's 2018 and we've just just recently got entity names from Wikipedia. I think Peter Norvig, having basically only machine translation to point to, is really going to eat crow when non-perceptual AI tasks sort of have nothing to do with stuff Google has developed. But what do I know.
I'm sure someone's going to trot out some obscure TPU or GPU-driven thing. It's been years! Awesome innovations in hardware really do lead to obvious, immediate crazy cool stuff. I'm really talking about the Kinect as an example here, in that it was really hyped and not much came of it. The TPU, and ML-specified hardware targeted to today's problems, is a slower-motion Kinect of our time.
Mining cryptocurrency, the most recent innovation, is the opposite of cool.
I'm confident these tools exist to capitalize on the subsidy from the gaming industry. AMD is wise to not chase ML features.