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Tesla turns on 10k-node Nvidia H100 Cluster

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Re: Tesla turns on 10k-node Nvidia H100 Cluster

#51

Post by ra7 »

toomuchtodo wrote: post #40
ComputerGuru wrote: post #21

Earlier quoted context omitted.

You are correct; it is, and flippant HN comments that are additionally incorrect are starting to become a thing. See the original tweet: https://twitter.com/SawyerMerritt/status/1696011140508045660

You’re being pedantic (rightfully so) and I’m being loose with words. While Dojo is the supercomputer Tesla built for vision training, I lumped anything contributing to their machine vision model training as Dojo. It’s called Dojo because that’s where the training takes place. https://en.wikipedia.org/wiki/Tesla_Dojo From the History section (although Technical Architecure is also worthy of consuming in its entirety)…

You’re just using it wrong. Dojo “supercomputer” specifically includes custom chips, which doesn’t exist yet.

Re: Tesla turns on 10k-node Nvidia H100 Cluster

#52

Post by [deleted] »

md_ wrote: post #50

I'm confused. The article from September 1 linked to here is strangely future-tense ("But the firm’s latest investment in 10,000 of the company’s H100 GPUs dwarfs the power of this supercomputer....This AI cluster, worth more than $300 million, will offer a peak performance..."). It links to a Tom's Hardware article ( https://www.tomshardware.com/news/teslas-dollar300-million-a... ) from August 28 that says "Tesla is…

[deleted]

Re: Tesla turns on 10k-node Nvidia H100 Cluster

#53

Post by tibbydudeza »

aik wrote: post #46
martin8412 wrote: post #16

Earlier quoted context omitted.

Vaporware, just like much of what Musk talks about.

What that he has talked about been vaporware?

That Telsa owners can use their cars to make money while they are working as robo taxis -let's just say he vastly underestimates effort it takes to make progress - FSD is not there yet.

Re: Tesla turns on 10k-node Nvidia H100 Cluster

#54

Post by jeffbee »

jdiez17 wrote: post #12

What happened to their custom hardware training stack Dojo? They had some interesting ideas there. The last I heard, they had one of those tiles "working" in the lab. Pretty far from a production setup. I can imagine they either underestimated the software effort needed to squeeze as much performance as possible out of those things, or they underestimated the pace at which Nvidia scales FLOPS/$, or both.

Dojo has always been a lie.

Re: Tesla turns on 10k-node Nvidia H100 Cluster

#55

Post by aik »

tibbydudeza wrote: post #53
aik wrote: post #46

Earlier quoted context omitted.

What that he has talked about been vaporware?

That Telsa owners can use their cars to make money while they are working as robo taxis -let's just say he vastly underestimates effort it takes to make progress - FSD is not there yet.

Vaporware assumes it will never happen. Is that the case you think or is it that he was vastly over optimistic? Very likely the latter.

Re: Tesla turns on 10k-node Nvidia H100 Cluster

#56

Post by kaycebasques »

n00b questions from someone just beginning to get interested in HPC

I see mention of using this supercomputer for training models. Is that the only purpose? What other types of things do orgs usually do with these supercomputers?

Are there any good boots-on-the-ground technical blogs that provide interesting detail on day-to-day experiences with these things?

Re: Tesla turns on 10k-node Nvidia H100 Cluster

#57

Post by awestroke »

mmcwilliams wrote: post #38
s1gnp0st wrote: post #27

Earlier quoted context omitted.

Reusable rockets, electric cars, solar panels... What would you say grants you the standing to opine here?

I'm fairly certain all of those existed prior to Musk's suggestion of them.

You’re also wrong

Re: Tesla turns on 10k-node Nvidia H100 Cluster

#58

Post by cactusplant7374 »

WendyTheWillow wrote: post #32
bluelightning2k wrote: post #30

It's funny - I'm listening to "The Founders" audiobook and right now they're telling the story of Elon Musk at PayPal wanting to rewrite for Windows server because Linux was too hard. Weird to think that his next company's compute platform is this.

Linux was a lot harder back then.

Harder for who? Elon certainly didn't have the technical chops to work with it.

Re: Tesla turns on 10k-node Nvidia H100 Cluster

#59

Post by aik »

jeffbee wrote: post #54
jdiez17 wrote: post #12

What happened to their custom hardware training stack Dojo? They had some interesting ideas there. The last I heard, they had one of those tiles "working" in the lab. Pretty far from a production setup. I can imagine they either underestimated the software effort needed to squeeze as much performance as possible out of those things, or they underestimated the pace at which Nvidia scales FLOPS/$, or both.

Dojo has always been a lie.

Source? The article mentions they now have / use both.

Re: Tesla turns on 10k-node Nvidia H100 Cluster

#60

Post by dahart »

queuebert wrote: post #47
dahart wrote: post #22

> This AI cluster, worth more than $300 million, will offer a peak performance of 340 FP64 PFLOPS for technical computing and 39.58 INT8 ExaFLOPS for AI applications, according to Tom’s Hardware. I was curious why this statement lead with fp64 flops (instead of fp32, perhaps), but I looked up the H100 specs, and NV’s marketing page does the same thing. They’re obviously talking about the H100 SXM here, which has the…

In the old days, depending on architecture, fp64 performance could be atrocious even when fp32 was decent, so bragging about fp64 performance has an authenticity to it. Not all scientific computing requires 64 bits, but knowing that you can drop to high precision when necessary without penalty is nice. Also, back in the day, integer ops were just called 'ops', grumble grumble. But yeah FLOPS specifically refers to fl…

Still true that fp64 throughput is lower for consumer GPUs - both NV and AMD. That’s kinda why I was curious about leading with that metric - outside of HPC and scientific applications, a lot of people don’t really need fp64, and the machine might normally have a much higher fp32 throughput.

> knowing you can drop to high precision when necessary without penalty is nice.

I guess I maybe don’t know why you’d ever have 1:1 fp32 and fp64 perf. Aren’t the fp64 multipliers (for example) basically 4x fp32 multipliers? I am under the possibly naive impression that if you have all the transistors for 1 fp64 core, that you’d end up with all the transistors you need for 2 or 4 fp32 cores. Maybe that’s not true today, but there does have to be at least 2x the transistors overall for 64-bit vs 32-bit, and lots of those should be shared or reusable, no? It doesn’t seem quite right to frame naturally higher 32-bit op throughput as a “penalty” on 64-bit ops. You’re asking the hardware to do more with 64, and it makes complete sense that given the exact same budget for bandwidth, energy, memory, compute, etc. that 32-bit ops would go faster, no? If the op throughput of fp64 and fp32 is the same, doesn’t that possibly imply that the fp32 ops are potentially being wasted / penalized, just for the sake of having matching numbers?

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