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Very much not an expert here but what I understand is that most deep learning frameworks (PyTorch, Tensorflow, etc.) have some overhead associated with them jus
by iaw 3y ago
Very much not an expert here but what I understand is that most deep learning frameworks (PyTorch, Tensorflow, etc.) have some overhead associated with them just being on the graphics card. This takes PyTorch code and removes the overhead by translating the network into a "native" language for the card (CUDA for NVIDIA).
What I'm not sure is what "HIP" is in this context.
The way I'm reading this is it's the difference between running code in an interpreter vs. on the bare metal (for the GPU)
- entropicdrifter 3y agoHIP is AMD's open-source re-implementation of CUDA libraries.
- viewtransform 3y agoHIP is AMD's contribution to the open source community to overcome Nvidia's CUDA software moat You write in HIP C++ language and run them on either NVIDIA or AMD platforms. This way you get cross-platform code and are not stuck with Nvidia. Use HIPify tool to automatically convert existing sources from CUDA to HIP. It's been around for many years - but the fact that so many people still don't know about it - speaks for the sad state of AMD communication. https://docs.amd.com/bundle/HIP-Programming-Guide-v5.3/page/Introduction_to_HIP_Programming_Guide.html https://docs.amd.com/bundle/HIP-Programming-Guide-v5.3/page/...
- my123 3y agoHIP is a pathetic CUDA API clone. Gratuitous renames don't do it any good and are more representative of NIH rather than anything else (sadly). They should have shipped a proper header set instead of hipify.
- deleted 3y ago[deleted]