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Their GPUs already have really good performance for machine learning tasks, but it doesn't seem like there's a whole lot more they can do about people overwhelm
by opencl 7y ago
Their GPUs already have really good performance for machine learning tasks, but it doesn't seem like there's a whole lot more they can do about people overwhelmingly using CUDA. Their ROCm software stack has gotten reasonably good but getting developers to buy into is hard with how much inertia NVIDIA/CUDA has.
- changoplatanero 7y agoWhy cant AMD make their gpus to be CUDA compatible?
- deleted 7y ago[deleted]
- sq_ 7y agoIf I remember correctly, CUDA is pretty tightly tied to Nvidia’s GPU architecture, so it would be very difficult to get the same things to run on AMD chips without them making huge changes to conform to Nvidia’s way of doing things. I think there have been a few projects that try to translate CUDA stuff into OpenCL or other AMD-compatible compute platforms.
- yalue 7y agoI'd say it's likely because NVIDA's CUDA compiler produces code for NVIDIA GPUs, and AMD would have a lot of (questionably legal) reverse engineering ahead of them in order to support the same code on their own GPUs. If you're asking why AMD doesn't make a compiler for CUDA source code that targets their own GPUs--that's basically what ROCm currently does. They're pushing their CUDA alternative, called "HIP", which is essentially just CUDA code with a find-and-replace of "cuda" with "hip". (And other similarly minor changes.) They have an open source "hipify" program that does this automatically (https://github.com/ROCm-Developer-Tools/HIP/tree/master/hipify-clang/ https://github.com/ROCm-Developer-Tools/HIP/tree/master/hipi...). So, basically, AMD GPUs are already sort of CUDA compatible: just run your CUDA code through hipify, then compile it using the HIP compiler, and run it on a ROCm-supported system (which, for now is the most spotty of all of these steps IMO).
- useful 7y agoROCm is supported natively in TF 2.0, so they will benefit from that.
- PeterisP 7y agoIs it? TF2.0 Alpha and Beta release notes don't mention anything about it, and the official docs at https://www.tensorflow.org/install/pip https://www.tensorflow.org/install/pip are quite explicit that the tensorflow-gpu supports only CUDA cards. The last time I looked at ROCm (which was something like a year ago) it was "supported" as in "there's reports on the internet that someone got it to work" but when I tried, I couldn't get it to work and it really wasn't worth the effort. If I'd dig out a machine with an AMD GPU right now, can I get it working (like, train MNIST or some other helloworld'y system) within an hour, and is there documentation available on how exactly that should be done?
- imtringued 7y agohttps://pypi.org/project/tensorflow-rocm/ https://pypi.org/project/tensorflow-rocm/