Hi, I am currently installing tensorflow via easybuild (I assume many of us do these days) and am trying to understand EasyBuild’s ideas on toolchains supporting cuda.
I looked at TensorFlow-1.5.0-goolfc-2017b-Python-3.6.3.eb, which builds ontop of a toolchain containing GCC, Cuda (installed as a compiler module), and OpenMPI, Blas, FFTW etc. I now noticed that there is a new TensorFlow-1.6.0-foss-2018a-Python-3.6.4-CUDA-9.1.85.eb, which is accepted into the development branch (PR 6016). This builds ontop a “vanilla” foss-2018a toolchain, using a Cuda and cuDNN modules installed as a core module (system compiler). I am wondering how do we want to organise us in future? Do we want to continue with the goolfc idea or do we go for a “core” cuda and cuDNN? I feel this needs standardising soonish. It is also something I feel I need to document for my users, who want to build their own cuda based software. What models should be loaded to build software. Any comments, how we take this further? Best wishes Joachim
