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Nvidia Grace CPU

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Re: Nvidia Grace CPU

#161

Post by kimixa »

simondotau wrote: post #158
messe wrote: post #35

Earlier quoted context omitted.

I wonder if Apple also intends to introduce ECC LPDDR5 on the Mac Pro. Other than additional expansion, I’m struggling to see what else they can add to distinguish it from the Mac Studio.

In order for an Apple Silicon Mac Pro to make any sense whatsoever, its SOC will need have to have support for off-package memory and substantially more PCI-E lanes than the M1 Ultra. Therefore it seems all but certain to me that it will debut the M2 chip family. Apple isn't going to give up the substantial performance benefits of on-package unified memory in order to support DIMMs. Therefore I predict that we'll see…

Currently the performance and power benefits of having tightly packaged RAM are taken full advantage of by the M1 family. A less tightly coupled memory system will likely have significant performance implications. There's a reason why all GDDR memory for GPUs is soldered, as there's signaling issues caused by things like longer traces and the electrical behavior of the sockets themselves.

People also seem often to forget that interconnects are a significant amount of modern power budgets - look at the Epic IO die often using more than the cores in many workloads. It may be the the M1 family looks less attractive when you actually have to add these requirements.

Perhaps there's some possibility of having both a tightly-coupled RAM package and also have an extensible memory system - though that has significant management complexity if you try to treat it like a cache, or likely needs app support if it's some NUMA system where they're mapped separately. But possible, at "just" the cost of the extra memory controller.

Re: Nvidia Grace CPU

#162

Post by ksec »

michaelt wrote: post #112
tyrfing wrote: post #78

Earlier quoted context omitted.

Discrete GPUs have historically been a relatively small and volatile niche compared to CPUs, it's only in the last few years that the market has seen extreme growth. edit: the market pretty much went from gaming as the primary pillar to gaming + HPC, which makes it far more attractive since you'd expect it to be much less cyclical and less price sensitive. Raja Koduri was hired in late 2017 to work on GPU related stu…

CUDA came out in 2007. Wikipedia puts the start of the GPU-driven 'deep learning revolution' in 2012 [1] and people have been putting GPUs into their supercomputers since 2012 as well [2] I find it strange that Intel has basically just left the entire market to nvidia, despite having 10-15 years warning and running their own GPU division the whole time . [1] https://en.wikipedia.org/wiki/Deep_learning#Deep_learning_r…

Competing with Nvidia on Gaming GPU wasn't something Intel were keen to do after their failure with i740. The Gaming market wasn't as big, and you are ultimately competing on Driver optimisation, not on actual hardware.

CUDA and Deep Learning may have started in 2007 and 2010. But their usage, or their revenue potential was unclear back then. Even in 2015, Datacenter revenue was less than one eighth of gaming revenue. And rumours of Google AI Processor ( now known as TPU ) started back in 2014 when they started hiring. In 2021, Datacenter is roughly equal to Gaming revenue, and are expected to exceed them in 2022.

Intel sort of knew GPGPU could be a threat by 2016 / 17 already. That is why they started assembling a team, and hired Raja Koduri in late 2017. But as with everything Intel in post Pat Gelsinger era, Intel was late to react. From Smartphone to Foundry Model and now GPGPU.

Re: Nvidia Grace CPU

#163

Post by shaklee3 »

pastaguy1 wrote: post #157
michaelt wrote: post #112

Earlier quoted context omitted.

CUDA came out in 2007. Wikipedia puts the start of the GPU-driven 'deep learning revolution' in 2012 [1] and people have been putting GPUs into their supercomputers since 2012 as well [2] I find it strange that Intel has basically just left the entire market to nvidia, despite having 10-15 years warning and running their own GPU division the whole time . [1] https://en.wikipedia.org/wiki/Deep_learning#Deep_learning_r…

They tried to check many, some, maybe possibly more of the boxes with the Xeon Phi, and it kinda seems like things simply didn't go their way. Cuda wasn't as flexible, and the payoff wasn't as big in 2010 or so as it is now. I've never used a phi, but i can see where they were coming from i think. No need for a full rewrite like Cuda (maybe). The hardware is also more flexible than a GPU, but that turned out to be le…

this isn't true. the phi was extremely complex to program for, and it was not simply a port of standard x86 code. it required you to pay attention to multiple levels of memory hierarchy, just as the GPU did.

Re: Nvidia Grace CPU

#164

Post by ceeplusplus »

dsign wrote: post #89
20220322-beans wrote: post #53

What are people's experience of developing with NVIDIA? I know what Linus thinks: https://www.youtube.com/watch?v=iYWzMvlj2RQ

I like CUDA, that stuff works and is rewarding to use. The only problem is the tons and tons of hoops one must jump to use it in servers. Because a server with a GPU is so expensive, you can't just rent one and have it running 24x7 if you don't have work for it to do, so you need a serverless or auto-scaling deployment. That increases your development workload. Then there is the matter of renting a server with GPU; t…

Luckily, you can run CUDA code on even a cheap GTX 1050, so you can test locally and run the full size job on a big V100/A100/H100 system.

Re: Nvidia Grace CPU

#166

Post by fulafel »

donkeydoug wrote: post #12

soooo... would something like this be a viable option for a non-mac desktop similar to the 'mac studio' ? def seems targeted at the cloud vendors and large labs... but it'd be great to have a box like that which could run linux.

As long as your application workload is a good match for the 144 ARM cores.

Re: Nvidia Grace CPU

#167

Post by BuckRogers »

tgtweak wrote: post #133
BuckRogers wrote: post #116

Earlier quoted context omitted.

While I view my Intel iGPU as a backup, I don't have any negative impressions about its performance like many gamers do. I have the 11900K which has an iGPU capable of 720P gaming. Which is quite remarkable to be honest considering it's integrated into my CPU. Cheap and "just works" is exactly how I view it, but they're getting better in the last 2 generations. I can't find a new dGPU at MSRP so I'm going to see if t…

GPU shortages are nearing an end and with next generation products from Nvidia, AMD and Intel on deck, well probably be in a really good spot for GPU consumers come q4 2022.

It’s been so long now, 2.5 years that I now view GPUs like I do gas prices. You can’t trust in a stable market. It’s not like GPUs didn’t skyrocket in price in the years leading up to the shortage anyway.

Best long term lifetime decision is to get off any dependency for either of them. I’m looking at electric cars and Intel NUCs. A lot of people that I know moved to laptops for the same reason. A lot of us gave up and many like me no longer trust the market.

Re: Nvidia Grace CPU

#168

Post by ribit »

bullen wrote: post #128
ribit wrote: post #103

Earlier quoted context omitted.

1030 has been dethroned a while ago. Apple G13 delivers 260GFLOPS/W in a general-purpose GPU. I mean, their phone has more GPU FLOPS than a 1030.

Nope, 1030 has 37 Gflops/W... G13 786/20W = 40... and that's 14nm vs 5nm... still I'm pretty sure there are things the 1030 can do that the A13 will struggle with. Game Over!

G13 (in the 8-core/1024 ALU config as in M1) delivers 2.6TFLOPS with sustained power consumption of 10W. That's almost an order of magnitude better than 1030. Sure, node definitely matters, but going from 14nm to 5nm cannot explain the massive power efficiency difference alone.

What are the things that 1030 can do that G13 will struggle with?

Re: Nvidia Grace CPU

#169

Post by hughrr »

astrange wrote: post #115
hughrr wrote: post #70

Earlier quoted context omitted.

No. Intel worked out it needs to open its production capacity to other vendors. They will end up another ARM fab with a legacy x86-64 business strapped on the side. That's probably not a bad place to be really. I think x86-64 will fizzle out in about a decade.

I don't feel like ARM has serious technical advantages over x86-64 as an ISA, although it is cleaner and has more security features which is good. Isn't the main advantage just that it's easier to license ARM? Once enough patents expire all ISAs are eventually equal, I'd think.

Spend some time looking at optimised compiler output on godbolt on both architectures. ARM has some really nice tricks up its sleeves.

I’ve been using ARM since about 1992 though so I may be biased.

Re: Nvidia Grace CPU

#170

Post by bullen »

zerohp wrote: post #132
bullen wrote: post #128

Earlier quoted context omitted.

Nope, 1030 has 37 Gflops/W... G13 786/20W = 40... and that's 14nm vs 5nm... still I'm pretty sure there are things the 1030 can do that the A13 will struggle with. Game Over!

Your numbers are completely wrong. The claim of 2.6 Tflops for the M1 was independently verified. https://www.realworldtech.com/forum/?threadid=197759&curpost...

There is not a single page on the whole internet that states Gflops and Watt on the same page, I did 2 googlings: "apple g13 gflops" and "apple g13 watt"... the results where completely disturbing seen this info should be clearly available. Like when you google 1030 gflops and watt you get all links on google linking to pages stating both figures and they are the same...

M1 comes is MANY flavours with different watt and gflops.

And for CPU Glops I had to get friends to measure it themself: 2.5Glops/W compared to Raspberry 4 2Gflops/W and this time it's 5nm vs 28nm.

Please give me official Gflops and Watt sources and we can discuss.

The page you link is NOT clearly stating watts in a clear way.

> What are the things that 1030 can do that G13 will struggle with?

I real life when you develop games for real hardware you notice their real limitations like fill rates and how they scale different behaviours because they have enough registers to do things in one blow or they have to remember things. It's complicated, but eventually you realize you can just benchmark things for your own needs and for me 1030 is for all purposes as good as 1050 so far: 2000 non-instanced animated characters on 1030 at 30W vs like 2500 for 80W 1050!

Without knowing, I'm pretty sure the M1 cannot do more than 1000 at whatever watt it uses... not that I would ever compile anything for a machine where I need to sign the executable.

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