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No one runs Cuda, everyone runs PyTorch. Which you can run on it.
So does it support cuda or not are are you gonna argue little things all day?
You do read the licenses of SDKs you use, right?
Nothing but Nvidia hardware will ever "support" CUDA.
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Buying Xilinx helped a lot here.
it's so true it hurts
What's your take on projects like https://github.com/corundum/corundum I'm trying to get better at FPGA design, perhaps learn PCIe and some such but Vivado is intimidating (as opposed to Yosys/nextpnr which you seem to hate) should I just get involved with a project like this to acclimatise somewhat?
> Intel Gaudi software integrates the PyTorch framework and provides optimized Hugging Face community-based models – the most-common AI framework for GenAI developers today. This allows GenAI developers to operate at a high abstraction level for ease of use and productivity and ease of model porting across hardware types. what is the programming interface here ? this is not CUDA right ...so how is this being done ?
PyTorch has a bunch of backends including CUDA, ROCm, OneAPI, etc.
This is a bit snarky — but will Intel actually keep this product line alive for more than a few years? Having been bitten by building products around some of their non-x86 offerings where they killed good IP off and then failed to support it… I’m skeptical. I truly do hope it is successful so we can have some alternative accelerators.
What’s Next: Intel Gaudi 3 accelerators' momentum will be foundational for Falcon Shores, Intel’s next-generation graphics processing unit (GPU) for AI and high-performance computing (HPC). Falcon Shores will integrate the Intel Gaudi and Intel® Xe intellectual property (IP) with a single GPU programming interface built on the Intel® oneAPI specification.
Yesterday I thought about installing and trying to use https://news.ycombinator.com/item?id=39372159 (Reor is an open-source AI note-taking app that runs models locally.) and feed it my markdown folder but I stop midway, asking myself "don't I need some kind of powerful GPU for that ?". And now I am thinking "wait, should I wait for `standard` pluggable AI computing hardware device ? Is that Intel Gaudi 3 something like that ?".
This is a bit snarky — but will Intel actually keep this product line alive for more than a few years? Having been bitten by building products around some of their non-x86 offerings where they killed good IP off and then failed to support it… I’m skeptical. I truly do hope it is successful so we can have some alternative accelerators.
One nice thing about this (and the new offerings from AMD) is that they will be using the "open accelerator module (OAM)" interface- which standardizes the connector that they use to put them on baseboards, similar to the SXM connections of Nvidia that use MegArray connectors to thier baseboards. With Nvidia, the SXM connection pinouts have always been held proprietary and confidential. For example, P100's and V100's…
Pascal series are cheap because they are CUDA compute capability 6.0 and lack Tensor Cores. Volta (7.0) was the first to have Tensor Cores and in many cases is the bare minimum for modern/current stacks. See flash attention, triton, etc as core enabling libraries. Not to mention all of the custom CUDA kernels all over the place. Take all of this and then stack layers on top of them... Unfortunately there is famously…
But my work/fun is in CFD. One of the main codes I use for work was written to be supported primarily at the time of Pascal. Other HPC stuff too that can be run via OpenCL, and is still plenty compatible. Things compiled back then will still run today; It's not a moving target like ML has been.
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Itanic was a fun era
Itanium only stuck around as long as it did because they were obligated to support HP.
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I'm not sure the prices would go up that much. What would anyone buy that card for? Yes, it has a decent memory bandwidth (~750 GB/s) and it runs CUDA. But it only has 16 GB and doesn't support tensor cores or low precision floats. It's in a weird place.
IDK, is it really that much more powerful than the P40, which is already fairly cheap?
The P40 was aimed at the image and video cloud processing market I think, and thus the GDDR ram instead of HBM, so it got more VRAM but at much less bandwidth.
I wonder if someone knowledgeable could comment on OneAPI vs Cuda. I feel like if Intel is going to be a serious competitor to Nvidia, both software and hardware are going to be equally important.
I'm not familiar with the particulars of OneAPI, but it's just a matter of rewriting CUDA kernels into OneAPI. This is pretty trivial for the vast majority of small (<5 LoC) kernels. Unlike AMD, it looks like they're serious about dogfooding their own chips, and they have a much better reputation for their driver quality.
Althought at least for Python JITs, Intel seems to also be doing something.
And then there is the graphical debugging experience for GPGPU on CUDA, that feels like doing CPU debugging.
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Honestly, I thought the same thing upon reading the name. I'm aware of the reference to Antoni Gaudí, but having the name sound so close to gaudy seems a bit unfortunate. Surely they must've had better options? Then again I don't know how these sorts of names get decided anymore.
to be fair intel is not known for naming things well.