Live data from Hacker News

Ryzen Threadripper Pro 3995WX Spotted

guru3d.com

161–170 of 170 posts

Re: Ryzen Threadripper Pro 3995WX Spotted

#161
post #85

Earlier quoted context omitted.

> What workloads are so massively parallel that they can use 64 cores of x86 but can’t use the thousands of CUDA cores on a Quadro card? Building software, for one. C compilers and python interpreters don't run on a GPU. Lots of stuff doesn't run on a GPU. In fact in practice the only things that run on a GPU are the tiny handful of known subproblems that the industry has collectively decided are "GPU problems". Like…

Disclaimer: I am not a HW designer, I could very well be wrong. It is true that there are tasks where threading matters, but still require a CPU rather than a GPU. I wonder however if these tasks do need full SSE/AVX etc. Couldn't these extensions be removed of the CPU cores and instead have the necessary work performed by the GPU? It would be interesting to produce statistics on how much these extensions are used in…

I think the opposite is where things need to go. Having a wide SIMD ALU quickly accessible from your CPU core is very useful, especially as it shares the same memory system and a much more flexible programming model that allows you to do everything in a single source.

Re: Ryzen Threadripper Pro 3995WX Spotted

#162
post #12

I feel like 64 cores is getting rather close to a tipping point: What workloads are so massively parallel that they can use 64 cores of x86 but can’t use the thousands of CUDA cores on a Quadro card? I’m sure right now there are workloads that just need particular x86 instructions, but that feels like a temporary problem. Am I wrong about that being a temporary problem (that would feel frustrating)? Are these cores j…

Split it into 32 4 core VMs and rent it out for 30$ a month?

Re: Ryzen Threadripper Pro 3995WX Spotted

#163
post #12

I feel like 64 cores is getting rather close to a tipping point: What workloads are so massively parallel that they can use 64 cores of x86 but can’t use the thousands of CUDA cores on a Quadro card? I’m sure right now there are workloads that just need particular x86 instructions, but that feels like a temporary problem. Am I wrong about that being a temporary problem (that would feel frustrating)? Are these cores j…

Chrome. Once chrome is setup for this, I’ll be ready for 128 cores.

Re: Ryzen Threadripper Pro 3995WX Spotted

#164

Earlier quoted context omitted.

Disclaimer: I am not a HW designer, I could very well be wrong. It is true that there are tasks where threading matters, but still require a CPU rather than a GPU. I wonder however if these tasks do need full SSE/AVX etc. Couldn't these extensions be removed of the CPU cores and instead have the necessary work performed by the GPU? It would be interesting to produce statistics on how much these extensions are used in…

I think the opposite is where things need to go. Having a wide SIMD ALU quickly accessible from your CPU core is very useful, especially as it shares the same memory system and a much more flexible programming model that allows you to do everything in a single source.

The programming model is not very flexible at the lowest level: one has to create all the software infrastructure to communicate with the GPU (which boils down to sending commands and receiving response). There are languages (like futhark, julia, or even python), which handle all that boilerplate transparently.

The main problem is, afaik, that there is not enough control about where the code will run in these languages. At some point, one will want to describe all the algorithms using a single language, and somehow describe how the workload will have to be distributed across all the processors, or at least that's what I've been thinking about for a while. Once you have that level of control, the need for a versatile CPU is less clear. Note that nowadays people seems happy with hybrid solutions where the code is scattered across several languages (eg, one for the main program and one for the shaders, or for the client side UI), so my position is maybe not very strong.

HW-wise, is it possible that integrated GPUs are the first steps toward an architecture where CPU and GPU have better interconnections (ie, larger communication bandwidth and smaller latency) to the point where SIMD becomes moot? There is also the SWAR approach, where one doesn't rely on intrinsic SIMD instructions, but instead emulate them (though it's probably not very realistic for floating point computation).

Some other ideas:

- Apple has this neural engine in their latest chips, which is basically dedicated HW for neural networks

- In the wild, people are getting more and more interested in building their custom ASICs to cut software's middle-man cost: for them, the CPU solution is not good enough

- Intel recently introduced a new matrix ops extension in their CPUs: maybe at some point they'll introduce full GPU capabilities directly baked in the CPU? I am a little worried about the resulting ISA.

Anyway, I am not an HW engineer, nor a very good software one. I only have a limited view of the difficulties in writing good, CPU or GPU efficient code. My first post was prompted by remembering the first "large scale" multicores CPUs 15 years ago (specifically the Ultrasparc T1) which wheren't SIMD heavy. The direction naturally shifted as progress was made on SIMD to try to compete with GPUs, when it seems to me that originally CPUs and GPUs were complementary.

I tend to support modular solutions, but I don't know how costly that would be in term of efficiency at the HW level.

Re: Ryzen Threadripper Pro 3995WX Spotted

#165
post #99
post #96

Earlier quoted context omitted.

> Building software Well, the problem with that is that no make system can utilise so much core. Even linux kernel, probably the biggest C project in mainstream use, can not consistently load even 16 cores with mostly handwritten makefiles. P.S. I do not say that building software is not CPU parallelisable in principles, I'm saying that regular make systems have trouble handing big number of parallel tasks in practic…

Bazel utilizes the cores near linearly. It even makes use of remote cores in an efficient manner for compiling c++. 128 thread and 256 thread machines are great if you also have enough ddr4 to let each gcc/clang do their thing.

The rumoured Threadripper Pro 3995WC (64c/128t but with 8-channel memory support) might solve that problem.

Re: Ryzen Threadripper Pro 3995WX Spotted

#166
post #12

I feel like 64 cores is getting rather close to a tipping point: What workloads are so massively parallel that they can use 64 cores of x86 but can’t use the thousands of CUDA cores on a Quadro card? I’m sure right now there are workloads that just need particular x86 instructions, but that feels like a temporary problem. Am I wrong about that being a temporary problem (that would feel frustrating)? Are these cores j…

In deep learning, preprocessing can be pretty heavy, and then you find yourself CPU-bounded and not making full use of your 4x2080 Ti.

Re: Ryzen Threadripper Pro 3995WX Spotted

#167
post #120

Earlier quoted context omitted.

Compared to 2-4TB max in a 2 socket server system, the 16 or 32GB/card you get on a GPU is pretty small. The other issue is loading that memory - PCIe 4 is still the transfer time bottleneck between GPU and main memory.

The part about no virtual memory is kind of incorrect though. It doesn't work exactly like on the CPU, but still.

I'm not totally up to speed on modern GPU's - do they have a MMU that handles page faults on non-resident pages like a CPU would?

My understanding is that the GPU memory models are different enough that what an OS traditionally calls "virtual memory" couldn't be implemented in the same way.

Re: Ryzen Threadripper Pro 3995WX Spotted

#168

Earlier quoted context omitted.

There might be some other cases for less ram. If the rumor that it supports rdimm or lrdimm modules is true then it could enable much easier ecc support since there are not a lot of ecc udimm options out there

Mostly ECC UDIMMs are limited in clock speed, but many can be comfortably overclocked. I presently have four 2666 MHz ECC UDIMMs overclocked to 3200 MHz in my TRX40 workstation (M391A2K43BB1-CTD if anyone is curious).

Do the RAM sticks require separate cooling?

Re: Ryzen Threadripper Pro 3995WX Spotted

#169

Earlier quoted context omitted.

Mostly ECC UDIMMs are limited in clock speed, but many can be comfortably overclocked. I presently have four 2666 MHz ECC UDIMMs overclocked to 3200 MHz in my TRX40 workstation (M391A2K43BB1-CTD if anyone is curious).

Do the RAM sticks require separate cooling?

No. For the most part heat spreaders on RAM are a gimmick (unless you’re pushing really high OC, which this is not).

Re: Ryzen Threadripper Pro 3995WX Spotted

#170
post #85

Earlier quoted context omitted.

> What workloads are so massively parallel that they can use 64 cores of x86 but can’t use the thousands of CUDA cores on a Quadro card? Building software, for one. C compilers and python interpreters don't run on a GPU. Lots of stuff doesn't run on a GPU. In fact in practice the only things that run on a GPU are the tiny handful of known subproblems that the industry has collectively decided are "GPU problems". Like…

Disclaimer: I am not a HW designer, I could very well be wrong. It is true that there are tasks where threading matters, but still require a CPU rather than a GPU. I wonder however if these tasks do need full SSE/AVX etc. Couldn't these extensions be removed of the CPU cores and instead have the necessary work performed by the GPU? It would be interesting to produce statistics on how much these extensions are used in…

Ooops, I didn't mean Xeon PHI, I meant an older design with many small x86 cores.

Xeon PHI on the other hand was the first host of AVX-512 instruction set. Sorry.

Post reply on HN