11–20 of 24 posts
I've been waiting years and will wait more for PyTorch etc to work under Mesa rather than install RocM
Honestly, the likes of OpenAI and Mosaic need to consider Nvidia a huge threat long term. Nvidia has shown time and time again, they will royally fuck over anyone they have to in order to drive profit. Then, if they dare talk negatively about them, they will just discontinue their access to hardware. Not saying AMD is a savior, but having only ONE option will lead to long term issues.
I've been waiting years and will wait more for PyTorch etc to work under Mesa rather than install RocM
Mesa is a 3D lib for GPU rendering, does it do compute like what Nvidia's GPU does? we're talking about Mesa has its own small kernels that run matrix muts in parallel at scale. As far as I can tell, Mesa at the moment is not going to work for any ML framework like pytorch etc.
Honestly, the likes of OpenAI and Mosaic need to consider Nvidia a huge threat long term. Nvidia has shown time and time again, they will royally fuck over anyone they have to in order to drive profit. Then, if they dare talk negatively about them, they will just discontinue their access to hardware. Not saying AMD is a savior, but having only ONE option will lead to long term issues.
GPT4 please port my CUDA to work on AMD
Honestly, the likes of OpenAI and Mosaic need to consider Nvidia a huge threat long term. Nvidia has shown time and time again, they will royally fuck over anyone they have to in order to drive profit. Then, if they dare talk negatively about them, they will just discontinue their access to hardware. Not saying AMD is a savior, but having only ONE option will lead to long term issues.
GPT4 please port my CUDA to work on AMD
Earlier quoted context omitted.
Mesa is a 3D lib for GPU rendering, does it do compute like what Nvidia's GPU does? we're talking about Mesa has its own small kernels that run matrix muts in parallel at scale. As far as I can tell, Mesa at the moment is not going to work for any ML framework like pytorch etc.
Mesa advertises support for OpenCL[1], so the idea of using it as an ML backend isn't ridiculous. But I can't speak to whether or not anybody has actually tried to make that work, or where it stands. [1]: https://www.khronos.org/opencl/
Somewhat related: starting a new Ubuntu-pytorch-cuda project? That’ll be 10-15 gigabytes, please. Is there some way to strip down the individual deps? I imagine it’s the way that it is because the drivers and the pytorch source are probably machine generated before compilation, to some extent. Is there any hope for triton becoming a lightweight interstitial frame in the codebase stack that can just allow me to do the…
Sure after the building the binary is HUGE. But I only have to build it once and cache it so that all my workstations and training servers can use it.
Honestly, the likes of OpenAI and Mosaic need to consider Nvidia a huge threat long term. Nvidia has shown time and time again, they will royally fuck over anyone they have to in order to drive profit. Then, if they dare talk negatively about them, they will just discontinue their access to hardware. Not saying AMD is a savior, but having only ONE option will lead to long term issues.
Yup - which is exactly what is going on in the cloud space right now.
Because AWS and GCP chose to innovate with their own accelerators, Nvidia heavily favoured Azure for a while. Recently, GCP seem to have capitulated somehow and so are back on the bandwagon. Oracle, of course, never had any hope of success in cloud without leaning on some form of non-technical manipulation, which is why they were the first on board with DGX Cloud.
Sadly I don't see AMD as the solution, since they too have associated themselves more with Azure than the other clouds.