231–240 of 444 posts
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Do you mean something like OpenCL?
Exactly. More resources might get applied to improving it.
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Intel doesn't seem to be able to execute. It's not just pumping out GPUs - for AI you need drivers, and the equivilent of CUDA and all the various libraries built on CUDA like cuDNN. They do have OneAPI but it hasn't caught on like CUDA in that space. It's kind of too bad since OneAPI is open and CUDA is not.
I can really see Intel figuring this out. A lot of people on HN talking about Intel as an also-ran just like they spoke about AMD before Zen. Raptor Lake is at 7nm and incredibly competitive there (~2700 single core on geekbench, taken with a pinch of salt). They’re still planning on being on 1.8nm/18A within 2 years, while at the same time ramping up their GPU efforts (albeit using TSMC for 4nm). Nvidia is very much…
What's also pretty interesting that they actually didn't sell more chips this quarter - they ... just pretty much doubled the prices (hence the huge margin). This is what having a monopoly looks like ! This is also why companies that manufacture their cards didn't report any uptick in profits. I'm wondering how this play out in some months ? Do they have any pricing power with respect to NVidia ? Or NVidia could just…
> This is what having a monopoly looks like ! As someone who has been in the AI/ML space for over a decade, and even had an AMD/Radeon card for more than half of that, I can't help but feel that this is partially AMD's own fault. For many, many years it seemed to me that AMD just didn't take AI/ML seriously whereas, for all it's faults, NVIDIA seemed to catch on very early that ML presented a tremendous potential mar…
Instead, they've been going after the CPU market (and winning), HPC/scientific computing (high FP64 performance, in contrast to Nvidia's focus on low-precision ML compute), and integrating Xilinx.
However, I agree that it's an unfortunate situation, and I hope AMD becomes competitive in this space soon.
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My impression was that they used "Efficient Market Hypothesis" to mean "the theory that free-market competition rapidly drives down prices and breaks up monopolies on its own".
> the theory that free-market competition rapidly drives down prices and breaks up monopolies on its own You mean a theory that no economic school actually believes? Not even Austrians would sign that.
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They’re all pretty motivated, they’ve been motivated for years, and almost nothing is happening. This situation isn’t exactly a poster child for the Efficient Markets Hypothesis. Every year just sounds like “Nvidia’s new consumer GPUs are adding new features, breaking previous performance ceilings, running games at huge resolutions and framerates. Their datacenter cards are completely sold out because they can spin s…
Are they motivated? Seems like a massive coincidence how the big two of the GPU world are cousins, and one has been having massive success on the CPU, the other on GPU/AI, and every attempt from both side to enter the other's niche has been pretty weak. AMD compute is nowhere compared to NVIDIA. NVIDIA wanted to buy ARM, has got its finger in RISC-V, but apart from that, they don't really care. To be fair AMD has don…
Their GPUs have been very performant for my research (DNN training). However, their VRAM could be much larger. In my mind CPU ram is very cheap (for 32GB, it is currently around $65). But their GPUs for DNN that I use oh HPC are always less than 32GB but the GPUs are very pricey. Does anyone know why they don't increase their VRAM capacity so I can test models that require higher VRAM? Is VRAM considerably more expen…
The good new is that Nvidia's high GPU prices motivate everyone (Intel, AMD, ARM, Google, etc.) to try and tackle the problem by making new chips, making more efficient use of current chips, etc. For all the distributed computing efforts that have existed (prime factorization, SETI@Home, Bitcoin, etc.), I'm surprised there isn't some way for gamers to rent out use of their GPU's when idle. It wouldn't be efficient, b…
The main reason why you need massive ammounts of fast VRAM in the first place is that the main limitation of AI is memory bandwidth. Can't simply distribute an algorithm that is already throughput limited by memory bandwidth and distribute it with awful latency and bandwidth and hope for any improvement.
Their GPUs have been very performant for my research (DNN training). However, their VRAM could be much larger. In my mind CPU ram is very cheap (for 32GB, it is currently around $65). But their GPUs for DNN that I use oh HPC are always less than 32GB but the GPUs are very pricey. Does anyone know why they don't increase their VRAM capacity so I can test models that require higher VRAM? Is VRAM considerably more expen…
It will be this way until they get a competitor.
Their GPUs have been very performant for my research (DNN training). However, their VRAM could be much larger. In my mind CPU ram is very cheap (for 32GB, it is currently around $65). But their GPUs for DNN that I use oh HPC are always less than 32GB but the GPUs are very pricey. Does anyone know why they don't increase their VRAM capacity so I can test models that require higher VRAM? Is VRAM considerably more expen…
Folks on Reddit's /r/pcmasterrace have been discussing this for years - the consensus seems to be that Nvidia could add more VRAM to its GPUs without too much additional cost - but they don't want to, in order to push higher spending businesses and consumers to buy their more expensive chips to get more VRAM at exponential higher costs.
That's their price differentiator. It's the reason for their profits. nVidia is now So yes it'd be nice if nVidia made it so there was no reason for their $40k AI cards to exist. But they aren't going to do that.