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> That's something you need to ask to your package manager. Making sure that all dependencies of a package (e.g. drivers, compilers, etc.) are installed is the

by adev_ 6y ago

> That's something you need to ask to your package manager. Making sure that all dependencies of a package (e.g. drivers, compilers, etc.) are installed is the package manager's job. No that's bullshit and it shows you never have done it. Tensorflow is CUDA only and does not run over AMD GPU. Because CUDA is proprietary and has a monopoly on GPGPU for now. It is such a big deal that AMD had to fork tensorflow and try to make their own version it in order to make it "partially" run over HIP. This naturally makes it behind upstream, buggy and partially updated [^1] CUDA is not portable and will never be. The sad truth is that, due to CUDA, a big majority of GPGPU programs are now vendor lock-in on Nvidia hardware. That is unacceptable, but it is like that. [^1]: https://github.com/ROCmSoftwarePlatform/tensorflow-upstream https://github.com/ROCmSoftwarePlatform/tensorflow-upstream

fluffything 6y ago
> It is such a big deal that AMD had to fork tensorflow and try to make their own version it in order to make it "partially" run over HIP. That's because HIP requires changes to the program source code, but AMD has managed to upstream those patches to other projects. If they haven't done that for Tensorflow, that's kind of their problem. Clang can compile CUDA code, and it has an AMDGpu backend. AMD could compile that CUDA code to SPIRV if they wanted. Intel and PGI do compile CUDA to x86-64 using LLVM without problems.