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Nvidia is proposing a beast of a CPU system for Windows PCs

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Re: Nvidia is proposing a beast of a CPU system for Windows PCs

#531

Earlier quoted context omitted.

> Lets systems optimize utilization based on need, rather than be confined to specific pools The trouble with this is that the different types of memory have different characteristics. Latency for ordinary system memory is actually better than it is for GDDR, because GDDR is optimized for bandwidth. RTX 5090 has 1.8TB/s of memory bandwidth with a 512-bit memory bus. The same bus width for DDR5-9600 would have better…

How about having a large pool of unified memory and expanding the next layer (L3?) of cache to accommodate more of the CPU's the low-latency RAM usage?

As a rule, increasing the size of cache increases its latency, and how much of it you can use is capped by the quality of your cache management algorithms and the latency of the level above it.

Since CPUs are highly optimized, both increasing the latency of the main memory and increasing the size of L3 will probably lead to larger L3 latency.

Re: Nvidia is proposing a beast of a CPU system for Windows PCs

#532

Earlier quoted context omitted.

There's only so high you can go because the game assets have a maximum quality. Maybe you'll be able to max out the 5090 but what about the next flagship GPU? You're also likely not going to maximize all of bandwidth, compute, etc. because one of them will likely be your bottleneck. And it might be different depending on the GPU, too.

Most games are strictly scaled on resolution due to how deferred pipelines run. This is exactly the slider to max or not max everything on a gpu for games. The more pixels the more memory and the more compute.

If you're rendering at native resolution, which many PC gamers do, going higher isn't significantly better because it just helps with antialiasing via supersampling. There's no point rendering so much more pixels just because you can, that's just a waste of electricity.

Re: Nvidia is proposing a beast of a CPU system for Windows PCs

#533

Earlier quoted context omitted.

There's only so high you can go because the game assets have a maximum quality. Maybe you'll be able to max out the 5090 but what about the next flagship GPU? You're also likely not going to maximize all of bandwidth, compute, etc. because one of them will likely be your bottleneck. And it might be different depending on the GPU, too.

Most games are strictly scaled on resolution due to how deferred pipelines run. This is exactly the slider to max or not max everything on a gpu for games. The more pixels the more memory and the more compute.

The more pixels, the more compute of fragments but not necessarily more memory. A fragment might hit the same texel as an adjacent fragment.

Certainly not more from main memory, and maybe not more from the vram either depending on how the pipeline goes.

It's not a linear slider.

Re: Nvidia is proposing a beast of a CPU system for Windows PCs

#534
post #427

Earlier quoted context omitted.

The M1 isnt particularly good at inference, so pretty much every major current competitor with a 256+ bit unified memory system is better: AMD Strix Halo, NVIDIA DGX Spark, possibly Intel Panther Lake

Sure, but none of these shipped before the M1. That was the first chip I encountered that managed to do something useful without a discrete GPU.

You were likely only using Intel systems then. AMD systems have had iGPUs capable of light gaming for a very long time. It took Intel a long time to get to that level, after M1 (2020).

Re: Nvidia is proposing a beast of a CPU system for Windows PCs

#535
post #429

Earlier quoted context omitted.

What? It's incredibly easy to take full use of memory bandwidth. For example, put proper volumetric smoke/fire/explosion sim in your game. But game developers don't do that because they are lazy.

No, we don’t do it because the tradeoff isn’t worth it. A gpu based particle sim is very difficult to do well - it’s easy (but computationally expensive) to do a volumetric sim, but when you want that simulation to interact with world geometry correctly it comes with an explosion in complexity and performance. I promise you want our games to look as good as you want them to look.

How does interaction with world geometry come with an explosion in complexity and performance? Advection has almost same cost regardless of if some cells are solid or not. It's one extra line in your shader + 1 bit per cell. JFA to build solid mask.

Re: Nvidia is proposing a beast of a CPU system for Windows PCs

#536

Earlier quoted context omitted.

That's a fairly obvious idea, not dumb at all, but unfortunately it doesn't seem to pan out. Trying to specialize an LLM in one area harms its 'cognition' in all areas. For instance, if you train a coding model without all the Shakespeare and soap operas and Wikipedia and pirated Stephen King books and ancient Roman history and whatever, you end up with a worse coding model. I'm not sure anyone really understands why…

https://www.ibm.com/think/topics/domain-specific-llm

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Re: Nvidia is proposing a beast of a CPU system for Windows PCs

#537

Earlier quoted context omitted.

> Nvidia can barely scrape together one Ubuntu release per Jetson generation Why would they do more? It's an LTS distro, the Nvidia drivers are updated for as long as the hardware's compute capability is supported. Nvidia's ARM drivers are updated constantly, and battle-tested as the backbone in hundreds of thousands of Grace ARM servers.

Yes it's an LTS, which means it only makes sense to build something on it early in its release cycle, so the platform itself needs to keep up with new releases. Orins will go EoL next year, so good luck with that. That's not even considering the lazy out tree patchwork support Nvidia does for their products on top of that. Maybe it's different in this case for Windows since it forces a rolling release, but I seriousl…

> That's not even considering the lazy out tree patchwork support Nvidia does for their products

For their ARM SOCs? Almost every single ARM OEM on the consumer market is begging you to use out-of-tree blobs for basic firmware support. Nvidia's stance isn't ideal but it's also not unique (or damning) to the rest of their ARM competitors.

Re: Nvidia is proposing a beast of a CPU system for Windows PCs

#538

Earlier quoted context omitted.

That's a fairly obvious idea, not dumb at all, but unfortunately it doesn't seem to pan out. Trying to specialize an LLM in one area harms its 'cognition' in all areas. For instance, if you train a coding model without all the Shakespeare and soap operas and Wikipedia and pirated Stephen King books and ancient Roman history and whatever, you end up with a worse coding model. I'm not sure anyone really understands why…

https://www.ibm.com/think/topics/domain-specific-llm

The article is not backed up by reality. Why would use anything but a domain-specific LLM, if they actually worked?

The author is probably confusing RAG with pretraining. You can RAG on PubMed but you can't arrive at a competitive model by pretraining solely on it.

Re: Nvidia is proposing a beast of a CPU system for Windows PCs

#539

Earlier quoted context omitted.

How about having a large pool of unified memory and expanding the next layer (L3?) of cache to accommodate more of the CPU's the low-latency RAM usage?

As a rule, increasing the size of cache increases its latency, and how much of it you can use is capped by the quality of your cache management algorithms and the latency of the level above it. Since CPUs are highly optimized, both increasing the latency of the main memory and increasing the size of L3 will probably lead to larger L3 latency.

We might even decide to put 32GB of high-latency cache on the system board and then 12GB of throughput-optimized main memory close to the GPU. ;)

Re: Nvidia is proposing a beast of a CPU system for Windows PCs

#540

Earlier quoted context omitted.

Very true, but I'll point out that even those 2000 full screen reads per second at 4k are only 4% of the 5090's bandwidth. Sacrificing some of that speed for a unified memory architecture seems like a good trade. Plus, DLSS can greatly reduce the bandwidth requirements for 4K gaming.

I'm being very, very conservative with my estimates here. Based on the renderers I know, I could have easily tweaked the numbers to go up to 8000 full screen texture reads per second. That doesn't include texture or geometry or BVH reads or any memory writes. That is all in addition to those operations.

But do you think you'll reach 1.8 TB/s?
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