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AMD Radeon VII: High-End 7nm Vega Video Card

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Re: AMD Radeon VII: High-End 7nm Vega Video Card

#61

Post by atq2119 »

Joky wrote: post #54
atq2119 wrote: post #43

Earlier quoted context omitted.

Your comment is extremely confused. Let's unpack some of the confusion... > NVIDIA’s scalar architecture NVidia doesn't have a scalar architecture in any meaningful sense of the word. Individual work items execute in warps, meaning (up to) 32 items execute the same instruction, at the same PC. If you have divergence, i.e. fewer than 32 items at the same instruction, you lose ALU throughput. This is the same as in AMD…

> NVidia doesn't have a scalar architecture in any meaningful sense of the word. While I agree with your post in general, I'm not totally in agreement here. If you look at the context in which G80 and CUDA were introduced, it has a significant scalar dimension: for a single "thread" writing an addition between two float3 ended up being executed as 3 separate additions on the scalar components of the vector. This was,…

This also applies to AMD GCN, though. So if you compare GCN to the earlier TeraScale architecture, you could argue (like a sibling comment does) that AMD's GCN is a scalar architecture and so is Nvidia's.

If you look at the actual hardware, though, they're clearly both vector architectures: each "core" has N SIMD-style lanes executing the same instruction simultaneously; it's just that each of those lanes corresponds to a different work item of the compute dispatch.

This applies equally to AMD's and Nvidia's architectures.

Re: AMD Radeon VII: High-End 7nm Vega Video Card

#62

Post by nradov »

dragontamer wrote: post #32
doctorpangloss wrote: post #18

Earlier quoted context omitted.

Probably Larabee. Too early and too expensive for its time.

The Japanese PEZY machine looks incredibly interresting. Too bad it is only used in that one super-computer. Its overall design sits somewhere between a GPU and CPU. Like a GPU, it supports 8-way hyperthreading (GPUs typically support 10. CPUs usually only support 2... maybe 4 for Larabee). Like a GPU, its programmed through an OpenCL-like language (I know you don't like that, but its how it works). However, the over…

Is PEZY still a going concern after the arrests?

Re: AMD Radeon VII: High-End 7nm Vega Video Card

#63

Post by twtw »

hajile wrote: post #47
opencl wrote: post #19

Earlier quoted context omitted.

There's no guarantee this won't have gimped FP64, Hawaii for example had 1/2 rate FP64 but the consumer cards were 1/8 speed. But even 1/8 would leave the 1/32 NVIDIA cards in the dust. If they don't gimp FP64 it won't leave a whole lot of reason to buy the MI50 for probably 10x the price.

What AMD needs right now is marketshare so more stuff gets written in something cross-platform instead of cuda. I'd imagine that 1/2 has at least been discussed at great length for this card.

It's looking like that "something cross-platform" will be cuda, given that AMD's latest approach is to implement a compiler to convert cuda to "hip."

Re: AMD Radeon VII: High-End 7nm Vega Video Card

#64

Post by lawrenceyan »

doctorpangloss wrote: post #10
dragontamer wrote: post #2

Its 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 d…

> Exceedingly few problems resemble image recognition.

It makes it extremely difficult to take any of what you just said seriously knowing that you made this statement.

Re: AMD Radeon VII: High-End 7nm Vega Video Card

#65

Post by twtw »

Cybiote wrote: post #58
frankchn wrote: post #55

Earlier quoted context omitted.

I am interested in seeing benchmarks regarding this. I believe this is true for models with truly huge embeddings, but otherwise if your models are even a little compute dense then GPUs are faster.

My experience is that you need the additional caveat of a streaming fairly homogeneous and highly parallelizable approach or the memory transfer, branching and communication overheads will eat away nearly all the GPU gains. I've also noticed that a lot of the time, people are comparing GPU to naive implementations (and sometimes, implementations written in dynamic languages) instead of to highly tuned BLAS or MKL imp…

> comparing GPU to naive implementations (and sometimes, implementations written in dynamic languages) instead of to highly tuned BLAS or MKL implementations

In your experience, are these comparisons using naive GPU implementations as well? If so, that still seems like a valuable comparison.

Re: AMD Radeon VII: High-End 7nm Vega Video Card

#66

Post by doctorpangloss »

lawrenceyan wrote: post #64
doctorpangloss wrote: post #10

Earlier quoted context omitted.

> 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 d…

> Exceedingly few problems resemble image recognition. It makes it extremely difficult to take any of what you just said seriously knowing that you made this statement.

I don't know dude, if there weren't such lucrative jobs for academics at places like Google and pharmaceutical research companies, the discourse wouldn't be so narrowly focused on doing blah blah neural networks on huge libraries of images and molecular hashes.

People with academic backgrounds would be less afraid to point out how much vaporware machine learning has produced. They'd take stock in that their tenure, or six year PhDs, give them an opportunity to not chase trends so aggressively. They'd shill online less, for some giant faceless corporation like Google.

I'm not going to shit on a bunch of great stuff people have made. But the scary thing is that Noam Chomsky is probably right, that AI science hasn't advanced much at all. That we're still in an AI winter where it matters, the science, despite all the money and attention.

Re: AMD Radeon VII: High-End 7nm Vega Video Card

#68

Post by lawrenceyan »

doctorpangloss wrote: post #66
lawrenceyan wrote: post #64

Earlier quoted context omitted.

> Exceedingly few problems resemble image recognition. It makes it extremely difficult to take any of what you just said seriously knowing that you made this statement.

I don't know dude, if there weren't such lucrative jobs for academics at places like Google and pharmaceutical research companies, the discourse wouldn't be so narrowly focused on doing blah blah neural networks on huge libraries of images and molecular hashes. People with academic backgrounds would be less afraid to point out how much vaporware machine learning has produced. They'd take stock in that their tenure, o…

> the discourse wouldn't be so narrowly focused on doing blah blah neural networks on huge libraries of images and molecular hashes.

Do you mind clarifying what exactly your issues are with these specific applications of machine learning? Is it that you think there isn't really any meaningful value that can be gained in working within these areas? Or is it just that you want people to spend more time researching a different topic that you think would be more interesting/compelling?

Re: AMD Radeon VII: High-End 7nm Vega Video Card

#69

Post by AlphaSite »

dogma1138 wrote: post #20
CoolGuySteve wrote: post #17

Earlier quoted context omitted.

I'm hoping a 8gb or 12 gb version comes out for $500 or so. 16gb seems like overkill for the next couple years of game releases.

They can’t do 8 GB there are no 2GB HBM2 modules apparently and they can’t cut the amount of modules without cutting the CUs in half. It’s essentially just to keep up some production volume this is their HPC die sold to the consumer market its the Titan V equivalent die of AMD minus the Tensor Cores just for much much cheaper. It’s likely going to be a flop gaming wise, 2x8 pin power connectors put it at 300W TDP wit…

The 2080 isn't great perf/w either, not like the 1080 was.

Re: AMD Radeon VII: High-End 7nm Vega Video Card

#70

Post by jMyles »

brokenmachine wrote: post #56
jMyles wrote: post #21

Perhaps a good candidate for mining coins like LivePeer (one of 8-10 actual solid blockchain projects IMO).

>LivePeer (one of 8-10 actual solid blockchain projects IMO) Interesting. Can anyone suggest a good curated list of solid blockchain projects?

I'm interested in an answer to this also. If you find one, let me know.

In my experience, the "Build the Free Web" events are usually selected on the basis of actual engineering and not hype; the presenters there are typically from projects that are pretty good.

I work at NuCypher, and I think our project is very much based in sanity and solid programming. I feel confident that people will actually use our token to build interesting distributed things.

When we attend blockchain-oriented conferences, there are a few projects whose teams we usually gravitate towards and who seem (at least to me) to have similar principles (less hype, more logic).

These include LivePeer, Fluence, and Origin (I'm not currently invested in any of those, but actually I think I want to change that).

In addition to actual crypto assets, I also think that the Python tooling is really coming of age and full of a lot of very sober and solid programming - most of the projects that Piper Merriam and Jason Carver touch are worth looking at.

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