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Nvidia CEO Introduces Nvidia Ampere Architecture, Nvidia A100 GPU

blogs.nvidia.com

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Re: Nvidia CEO Introduces Nvidia Ampere Architecture, Nvidia A100 GPU

#101

Post by Klinky »

hyperbovine wrote: post #95
lightcatcher wrote: post #45

Earlier quoted context omitted.

> Intel keeps getting it right with numerical libraries. They're open. They work well. They work on AMD. What Intel numerical libraries are you thinking of? When I think of Intel numerical libraries, the first that comes to mind is MKL. MKL is neither open-source nor does it work well on AMD without some fragile hacks [0]. [0] https://www.pugetsystems.com/labs/hpc/How-To-Use-MKL-with-AM...

Well, OP didn't say MKL works well on AMD. But you can at least run it on a non-Intel CPU. Compare CUDA.

CUDA appears to have come out well before even OpenCL. I don't see why there would be expectation that nVidia would design their framework to work on a competitors product.

Re: Nvidia CEO Introduces Nvidia Ampere Architecture, Nvidia A100 GPU

#103

Post by fluffything »

hyperbovine wrote: post #95
lightcatcher wrote: post #45

Earlier quoted context omitted.

> Intel keeps getting it right with numerical libraries. They're open. They work well. They work on AMD. What Intel numerical libraries are you thinking of? When I think of Intel numerical libraries, the first that comes to mind is MKL. MKL is neither open-source nor does it work well on AMD without some fragile hacks [0]. [0] https://www.pugetsystems.com/labs/hpc/How-To-Use-MKL-with-AM...

Well, OP didn't say MKL works well on AMD. But you can at least run it on a non-Intel CPU. Compare CUDA.

The nvidia pgi compiler compiles CUDA to multi-core x86-64. There are other third-party compilers for CUDA->x86-64 (one LLVM-based one from Intel).

There is a "library replacement" for CUDA from AMD called HIP, that you can use to map CUDA programs to ROCm. But... it doesn't work very well.

NVIDIA also open-sourced CUDA support for Clang and LLVM. So anybody can extend clang to map CUDA to any hardware supported by LLVM, including SPIRV. The only company that would benefit from doing this would be AMD, but AMD doesn't have many LLVM contributors.

Intel drives clang and LLVM development for x86_64, paying a lot of people to work on that.

Re: Nvidia CEO Introduces Nvidia Ampere Architecture, Nvidia A100 GPU

#104

Post by ethbro »

johncalvinyoung wrote: post #92
pjmlp wrote: post #79

Earlier quoted context omitted.

That is what Intel tried to do with Larabee and failed spectacularly.

I wouldn't say they failed. I'd say they gave up on it before product maturity.

I'd say they aimed for the wrong market (graphics processing, where they were competing against very specialized and experienced competitors) and failed to partner.

Maybe Intel ~1998 could have solo-launched a new architecture, but the only way they'd get uptake now is something in cooperation with AMD.

And maybe the AMD partnership bridge is burnt from previous shenanigans, but it seems like both AMD and Intel would have incentive in more tightly coupling graphics compatibility to CPU ISA, vs Nvidia designing their own.

That said, in that hypothetical reality, Nvidia wouldn't have been able to innovate and execute nearly as fast as they have.

As one of my Comp-E professors once quipped, "If a structural engineer ever tells you programming close to processors is easy, ask them how they'd like their job if the physical properties of lumber changed every 2 years."

Re: Nvidia CEO Introduces Nvidia Ampere Architecture, Nvidia A100 GPU

#105

Post by fxtentacle »

wegs wrote: post #23
xvilka wrote: post #16

Probably even more closed than ever. They tend to become more and more restrictive with every new hardware generation. I wonder where their promised open source announcement they preannounced before.

Yeah. That's been my general problem with adopting NVidia for anything. They make good hardware, but there's a lot of lock-in, and not a lot of transparency. That introduces business risk. I'm not in a position where I need GPGPU, but if there wasn't that risk, and generally there were mature, open standards, I'd definitely use it. The major breakpoint would be when libraries like Numpy do it natively, and better yet…

Pretty much everyone these days uses a library for driving the GPU calculations. And they tend to either support multiple hardware targets directly (TensorFlow) or have API-compatible replacements (CuPy/NumPy).

So the lock-in risk here is that you might have to run your stuff on CPU if future NVIDIA GPUs are too overpriced.

I mean they are super expensive. But there's nothing that comes close to their cuBLAS library in terms of performance. So unless AMD ponys up and hires GPU algorithm engineers, NVIDIA will win simply due to their superior driver software.

I once had to optimize a CPU matrix multiplication algorithm. 10 days of work for a 2x speedup. Now imagine doing that for every one of the thousands of functions in the Blas library...

Re: Nvidia CEO Introduces Nvidia Ampere Architecture, Nvidia A100 GPU

#106

Post by solidasparagus »

wegs wrote: post #31
pjmlp wrote: post #25

Earlier quoted context omitted.

The large majority of researchers and business getting into NVidia products doesn't seem to find it that relevant, rather what tools, GPU programming languages and hardware they are able to put their hands on.

It's irrelevant to researchers. Research operates on rapid cycles: prototype, publish, move on. It does impact businesses. It doesn't prevent adoption for e.g. deep learning, but I haven't seen e.g. GPU-based databases reach broad adoption, or many other places where MIMD/SIMD would reduce costs or improve performance. Using classical hardware is clearly cheaper than the business risk and engineering time of relying…

> I haven't seen e.g. GPU-based databases reach broad adoption

Because it's very questionable whether GPU-based databases are generally valuable. GPUs accelerate compute, not all of the other things that databases do and often GPUs are not cost effective.

> I dabble in GPU, but never beyond prototypes, for those reasons

And I bet if you dabbled a little further you still wouldn't use it because it isn't cost-effective outside of intensive-compute applications.

> Technically, it makes sense. If I type a list comprehension in Python, it would run at higher speed and lower power on a SIMD or MIMD platform.

This is a very questionable claim. There are tradeoffs to these things (e.g. clock-speed, startup time, etc) and your list comprehensions are probably not compute heavy enough that the tradeoffs are worth it.

Re: Nvidia CEO Introduces Nvidia Ampere Architecture, Nvidia A100 GPU

#107

Post by Miraste »

Keyframe wrote: post #42

5 petaflops in DGX? That alone would put one of those babies into TOP500 top 50, and a superPOD would make no. 1, no? Well, if it could do that performance on Linpack/Rmax.

Less than that in double precision. If my math is right, they manage around 0.4 petaflops. Their previous-gen SuperPOD was #22. If they do indeed add four of the new ones that will still put it at #1, with something like 230 petaflops.

Re: Nvidia CEO Introduces Nvidia Ampere Architecture, Nvidia A100 GPU

#108

Post by fluffything »

wegs wrote: post #31
pjmlp wrote: post #25

Earlier quoted context omitted.

The large majority of researchers and business getting into NVidia products doesn't seem to find it that relevant, rather what tools, GPU programming languages and hardware they are able to put their hands on.

It's irrelevant to researchers. Research operates on rapid cycles: prototype, publish, move on. It does impact businesses. It doesn't prevent adoption for e.g. deep learning, but I haven't seen e.g. GPU-based databases reach broad adoption, or many other places where MIMD/SIMD would reduce costs or improve performance. Using classical hardware is clearly cheaper than the business risk and engineering time of relying…

> but I haven't seen e.g. GPU-based databases reach broad adoption

NVIDIA announced today that Apache Spark 3.0 is built on RAPIDS and showed some benchmarks claiming same perf at 1/5 the cost.

Not your classical database application though.

Re: Nvidia CEO Introduces Nvidia Ampere Architecture, Nvidia A100 GPU

#109

Post by jabl »

johncalvinyoung wrote: post #92
pjmlp wrote: post #79

Earlier quoted context omitted.

That is what Intel tried to do with Larabee and failed spectacularly.

I wouldn't say they failed. I'd say they gave up on it before product maturity.

They pivoted it to HPC (the Xeon Phi product line), produced a couple of generations of products, but that didn't really pan out either so they cancelled it.

I suppose some of the "DNA" lives on in AVX-512..

Re: Nvidia CEO Introduces Nvidia Ampere Architecture, Nvidia A100 GPU

#110

Post by jabl »

Keyframe wrote: post #42

5 petaflops in DGX? That alone would put one of those babies into TOP500 top 50, and a superPOD would make no. 1, no? Well, if it could do that performance on Linpack/Rmax.

A previous generation superPOD (with V100 GPU's) is currently at #20. Watch this space...
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