4 ms·

I've been thinking that NVDA stock is massively overpriced - yes, AI is a hot topic, but their only advantage is the software stack. It is just a matter of time

I've been thinking that NVDA stock is massively overpriced - yes, AI is a hot topic, but their only advantage is the software stack. It is just a matter of time until Intel and AMD realize that they should join hands and do an open-source CUDA alternative for their respecitve GPUs (yes, Intel has competetive GPUs and just like AMD and Nvidia they will try to get a share of the AI chip market share).

airstrike 2y ago
"just" a matter of time... If it were that easy, it would have already been done, or so they say. Also don't forget network effects
wmf 2y ago
They've been working on that for years.
- dylan604 2y ago
  Yeah? And? So? As if CUDA was developed overnight and never worked on again. Such a weak comment
  - zokier 2y ago
    AMD has been working on GPGPU at least as long as nVidia. AMDs "CTM" SDK was released in 2006, same year as CUDA. In 2007 they released Stream SDK. Then they had "APP SDK" for a while, which iirc coincided with their opencl phase. And now they landed on rocm. Meanwhile nvidia has kept trucking with just CUDA.
RyanShook 2y ago
2024 YTD returns: NVDA 172% AMD 27% INTC -30%
- deleted 2y ago
  [deleted]
- cj 2y ago
  Stocks of companies that develop extremely niche and technical things is a tiny sliver of the stock market that I actually think communities like HN would be better at valuing than the market. Technology stocks are the only ones I personally day trade for that reason. Example: at the beginning of a pandemic lockdowns, any HN user could have anticipated increased internet usage and buy Cloudflare/Fastly stock and made a lot of money before the rest of the market realized that CDN companies will significantly benefit from that specific macro event. I'm not convinced the market (or market analysts) have a deep understanding of Nividia's long-term advantage. If they did, we would have seen a much slower and steadier valuation increase rather than the meteoric rise. Meteoric stock price rise/fall = the market is having trouble valuing the stock. In other words, stock prices don't add much to the conversation.
  - storyinmemo 2y ago
    Intel's profit, and revenue, have declined for 3 consecutive years. Their price to earnings ratio is 36. Nvidia's revenue is now greater than Intel's with 20% of the employees that Intel has. Their PE ratio is 78, roughly double that of Intel. The market valued Nvidia as growing and Intel as not.
    - deleted 2y ago
      [deleted]
breggles 2y ago
"AMD is among several companies contributing to the development of an OpenAI-led rival to Cuda, called Triton, which would let AI developers switch more easily between chip providers. Meta, Microsoft and Intel have also worked on Triton." Last paragraph
- singhrac 2y ago
  This is a bit misleading since Triton is a bit higher level than CUDA. But the idea is kind of right - there’s active development of AMD and Intel backends, and Pytorch is investing into Triton as well.
nabla9 2y ago
> Intel has competitive GPUs No they don't. Both Intel and AMD compare their newest GPU favorably against Nvidia's H100 that has been on the market longer and soon to be replaced and then it's never H100 NVL for a reason. Intel and AMD can sell their GPU's only with lower profit margin. If they could match FLOPS per total ownership they would sell much better. Both are years behind.
- latchkey 2y ago
  Benchmarks were just run, MI300x is onpar/better than an H100. Next generation of MI (MI325x) is coming out end of the year and those specs look fantastic too. Especially on the all important memory front. 288GB is fantastic. Both companies will leapfrog each other with new releases. Anyone who believes that there should only be a single vendor for all AI compute will quickly find themselves on the wrong side of history
  - nabla9 2y ago
    Comparisons against H100 I have seen are always: 8x AMD MI300X (192GB, 750W) 8x H100 SXM5 (80GB, 700W) Never against 8x H100 NVL (188GB, <800W) What the customer does not see is how AMD must spend 2 times more money to produce a chip that is competitive against architecture that is soon 2 years old.
    - latchkey 2y ago
      > Never against 8x H100 NVL (188GB, <800W) Probably because they aren't widely available yet. It is also a dual card to get that much memory, which is still less than 192GB and far less than 288GB. https://www.anandtech.com/show/18780/nvidia-announces-h100-nvl-max-memory-server-card-for-large-language-models https://www.anandtech.com/show/18780/nvidia-announces-h100-n... > What the customer does not see is how AMD must spend 8-10 times more money to produce a chip that is competitive against architecture that is soon 2 years old. Source?
    - claytonjy 2y ago
      as sibling mentioned the 188GB is for a pair. The memory bump is from enabling the 6th block of memory that is otherwise disabled on H100s. I assume an "NVL box" is still 8 total GPUs, so more like 8x H100 NVL (94GB, 800W) the AMD box has a lot more GPU memory
dehrmann 2y ago
NVDA's moat is over-stated. There are several deep-pocketed players with pretty good AI chips. The big players are training models at such a large scale that they can afford to back them by different architectures. Smaller players use frameworks like Pytorch and Tensorflow, but those are backed by big players buying from Nvidia. But valuation isn't the NVDA trade right now; it's that there's still a bigger fool.
rib3ye 2y ago
NVDA P/E ratio 78.70 AMD P/E ratio 263.25 If NVDA is overpriced, AMD is REALLY over-priced.
- hmm37 2y ago
  AMD PE ratio is that high due to their purchase of Xilinx. It's forward PE ratio is much much lower, in the 50s.
  - drexlspivey 2y ago
    I'm curious, how does the all-stock acquisition that closed 2.5 years ago affect their trailing P/E but not their forward P/E ?
    - staticman2 2y ago
      Different accounting methods from what I gather. The acquisition is being accounted for over a 5 year period for the trailing p/e but not being included in the forward p/e over this 5 year period. This really shows how p/e is not a great metric in a vacuum.
      - lostmsu 2y ago
        Thank you all guys for the explanation. I was very puzzled seeing AMD p/e as a complete dilettante in finance reporting.
- rubatuga 2y ago
  When you see p/e mentioned in a debate run far away.
  - swores 2y ago
    I wish people wouldn't post such pointless comments - the only users who get any value from reading your sentence are people who already share your view and can go "hah yeah!", while you couldn't be bothered to explain why it's your view to anyone who doesn't already think the same thing. Literally no benefit over not saying anything. Sorry to be blunt.
cityofdelusion 2y ago
Problem is the CUDA advantage is gigantic and it has been known for years in GPGPU processing, way before AI was a meme. AMD has lost countless developers over the year just on hello world style projects. Developers had a solid 6-7 years of living with OpenCL when the green rival had a very mature and nice CUDA sitting there. I’ve been out of that world for a while now, but it was truly painful and turned a lot of devs off programming AMD devices. Now there’s a big moat of entrenched developers that could take decades to displace. It’s like trying to displace C++ with Java 22 — possible, but it’s a slow, slow trudge and everyone still remembers Java 1.4
- YetAnotherNick 2y ago
  No, the amount of code written in CUDA for pytorch could easily be rewritten in CUDA for few million or tens of millions of investment. The problem is that it is damn near impossible to get good performance in AMD. For complicated CUDA programs like flash attention(few 100 lines of code), no amount of developers could write those few 100 lines for AMD to get the same performance.
  - pzo 2y ago
    Even worse: GPGPU is not only about LLM or even ML. It's also for computer vision, signal processing, pointcloud processing, e.g. Opencv has backend for CUDA, open3d, PCL the same. Even apple is kind of worse than AMD regarding ecosystem of libraries and open source high performance algorithms - when I tried to port some ICP pipeline to apple metal there was nothing there, most libraries and research code target only CUDA
- pjmlp 2y ago
  While I agree with the sentiment towards CUDA, the example is a bit off, given that C++ basically lost all mindshare in distributed computing, to Java and others, and is hardly visible in CNCF projects landscape. Displacing C++ in compiler development and HFT/HPC/GPGPU with Java 22, most likely not happening, everwhere else it has been loosing mindshare, the current cybersecurity laws versus WG21 attitude towards them, doesn't help.
postmeta 2y ago
pytorch already supports AMD with device=cuda already opensourced ROCm/HIP https://github.com/pytorch/pytorch/blob/fb8876069d89aaf27cc9dace075dd36b8e7df4c7/docs/source/notes/hip.rst#hip-interfaces-reuse-the-cuda-interfaces https://github.com/pytorch/pytorch/blob/fb8876069d89aaf27cc9...
throwaway2037 2y ago
In my view, LLM is just the first step in the AI journey. The LLM boom will help NVidia to grow very fast and increase R&D. During this time, I expect new AI leaps that are not LLM-related. To be clear: I'm not talking about AGI, but rather, other practical advances.

airstrike 2y ago

"just" a matter of time... If it were that easy, it would have already been done, or so they say. Also don't forget network effects

wmf 2y ago

They've been working on that for years.

dylan604 2y ago
Yeah? And? So? As if CUDA was developed overnight and never worked on again. Such a weak comment
- zokier 2y ago
  AMD has been working on GPGPU at least as long as nVidia. AMDs "CTM" SDK was released in 2006, same year as CUDA. In 2007 they released Stream SDK. Then they had "APP SDK" for a while, which iirc coincided with their opencl phase. And now they landed on rocm. Meanwhile nvidia has kept trucking with just CUDA.

RyanShook 2y ago

2024 YTD returns: NVDA 172% AMD 27% INTC -30%

deleted 2y ago
[deleted]
cj 2y ago
Stocks of companies that develop extremely niche and technical things is a tiny sliver of the stock market that I actually think communities like HN would be better at valuing than the market. Technology stocks are the only ones I personally day trade for that reason. Example: at the beginning of a pandemic lockdowns, any HN user could have anticipated increased internet usage and buy Cloudflare/Fastly stock and made a lot of money before the rest of the market realized that CDN companies will significantly benefit from that specific macro event. I'm not convinced the market (or market analysts) have a deep understanding of Nividia's long-term advantage. If they did, we would have seen a much slower and steadier valuation increase rather than the meteoric rise. Meteoric stock price rise/fall = the market is having trouble valuing the stock. In other words, stock prices don't add much to the conversation.
- storyinmemo 2y ago
  Intel's profit, and revenue, have declined for 3 consecutive years. Their price to earnings ratio is 36. Nvidia's revenue is now greater than Intel's with 20% of the employees that Intel has. Their PE ratio is 78, roughly double that of Intel. The market valued Nvidia as growing and Intel as not.
  - deleted 2y ago
    [deleted]

breggles 2y ago

"AMD is among several companies contributing to the development of an OpenAI-led rival to Cuda, called Triton, which would let AI developers switch more easily between chip providers. Meta, Microsoft and Intel have also worked on Triton." Last paragraph

singhrac 2y ago
This is a bit misleading since Triton is a bit higher level than CUDA. But the idea is kind of right - there’s active development of AMD and Intel backends, and Pytorch is investing into Triton as well.

nabla9 2y ago

> Intel has competitive GPUs No they don't. Both Intel and AMD compare their newest GPU favorably against Nvidia's H100 that has been on the market longer and soon to be replaced and then it's never H100 NVL for a reason. Intel and AMD can sell their GPU's only with lower profit margin. If they could match FLOPS per total ownership they would sell much better. Both are years behind.

latchkey 2y ago
Benchmarks were just run, MI300x is onpar/better than an H100. Next generation of MI (MI325x) is coming out end of the year and those specs look fantastic too. Especially on the all important memory front. 288GB is fantastic. Both companies will leapfrog each other with new releases. Anyone who believes that there should only be a single vendor for all AI compute will quickly find themselves on the wrong side of history
- nabla9 2y ago
  Comparisons against H100 I have seen are always: 8x AMD MI300X (192GB, 750W) 8x H100 SXM5 (80GB, 700W) Never against 8x H100 NVL (188GB, <800W) What the customer does not see is how AMD must spend 2 times more money to produce a chip that is competitive against architecture that is soon 2 years old.
  - latchkey 2y ago
    > Never against 8x H100 NVL (188GB, <800W) Probably because they aren't widely available yet. It is also a dual card to get that much memory, which is still less than 192GB and far less than 288GB. https://www.anandtech.com/show/18780/nvidia-announces-h100-nvl-max-memory-server-card-for-large-language-models https://www.anandtech.com/show/18780/nvidia-announces-h100-n... > What the customer does not see is how AMD must spend 8-10 times more money to produce a chip that is competitive against architecture that is soon 2 years old. Source?
  - claytonjy 2y ago
    as sibling mentioned the 188GB is for a pair. The memory bump is from enabling the 6th block of memory that is otherwise disabled on H100s. I assume an "NVL box" is still 8 total GPUs, so more like 8x H100 NVL (94GB, 800W) the AMD box has a lot more GPU memory

dehrmann 2y ago

NVDA's moat is over-stated. There are several deep-pocketed players with pretty good AI chips. The big players are training models at such a large scale that they can afford to back them by different architectures. Smaller players use frameworks like Pytorch and Tensorflow, but those are backed by big players buying from Nvidia. But valuation isn't the NVDA trade right now; it's that there's still a bigger fool.

rib3ye 2y ago

NVDA P/E ratio 78.70 AMD P/E ratio 263.25 If NVDA is overpriced, AMD is REALLY over-priced.

hmm37 2y ago
AMD PE ratio is that high due to their purchase of Xilinx. It's forward PE ratio is much much lower, in the 50s.
- drexlspivey 2y ago
  I'm curious, how does the all-stock acquisition that closed 2.5 years ago affect their trailing P/E but not their forward P/E ?
  - staticman2 2y ago
    Different accounting methods from what I gather. The acquisition is being accounted for over a 5 year period for the trailing p/e but not being included in the forward p/e over this 5 year period. This really shows how p/e is not a great metric in a vacuum.
    - lostmsu 2y ago
      Thank you all guys for the explanation. I was very puzzled seeing AMD p/e as a complete dilettante in finance reporting.
rubatuga 2y ago
When you see p/e mentioned in a debate run far away.
- swores 2y ago
  I wish people wouldn't post such pointless comments - the only users who get any value from reading your sentence are people who already share your view and can go "hah yeah!", while you couldn't be bothered to explain why it's your view to anyone who doesn't already think the same thing. Literally no benefit over not saying anything. Sorry to be blunt.

cityofdelusion 2y ago

Problem is the CUDA advantage is gigantic and it has been known for years in GPGPU processing, way before AI was a meme. AMD has lost countless developers over the year just on hello world style projects. Developers had a solid 6-7 years of living with OpenCL when the green rival had a very mature and nice CUDA sitting there. I’ve been out of that world for a while now, but it was truly painful and turned a lot of devs off programming AMD devices. Now there’s a big moat of entrenched developers that could take decades to displace. It’s like trying to displace C++ with Java 22 — possible, but it’s a slow, slow trudge and everyone still remembers Java 1.4

YetAnotherNick 2y ago
No, the amount of code written in CUDA for pytorch could easily be rewritten in CUDA for few million or tens of millions of investment. The problem is that it is damn near impossible to get good performance in AMD. For complicated CUDA programs like flash attention(few 100 lines of code), no amount of developers could write those few 100 lines for AMD to get the same performance.
- pzo 2y ago
  Even worse: GPGPU is not only about LLM or even ML. It's also for computer vision, signal processing, pointcloud processing, e.g. Opencv has backend for CUDA, open3d, PCL the same. Even apple is kind of worse than AMD regarding ecosystem of libraries and open source high performance algorithms - when I tried to port some ICP pipeline to apple metal there was nothing there, most libraries and research code target only CUDA
pjmlp 2y ago
While I agree with the sentiment towards CUDA, the example is a bit off, given that C++ basically lost all mindshare in distributed computing, to Java and others, and is hardly visible in CNCF projects landscape. Displacing C++ in compiler development and HFT/HPC/GPGPU with Java 22, most likely not happening, everwhere else it has been loosing mindshare, the current cybersecurity laws versus WG21 attitude towards them, doesn't help.

postmeta 2y ago

pytorch already supports AMD with device=cuda already opensourced ROCm/HIP https://github.com/pytorch/pytorch/blob/fb8876069d89aaf27cc9dace075dd36b8e7df4c7/docs/source/notes/hip.rst#hip-interfaces-reuse-the-cuda-interfaces https://github.com/pytorch/pytorch/blob/fb8876069d89aaf27cc9...

throwaway2037 2y ago

In my view, LLM is just the first step in the AI journey. The LLM boom will help NVidia to grow very fast and increase R&D. During this time, I expect new AI leaps that are not LLM-related. To be clear: I'm not talking about AGI, but rather, other practical advances.