ptrblck:

Since it seems you have limited right on this machine, you could check if any CUDA samples can be compiled and executed and might be able to use a docker container as a workaround (however, which could also fail given that the driver might not be installed correctly).


Most of CUDA samples can be compiled and executed, like 0_Simple/vectorAdd, 6_Advanced/eigenvalues and 7_CUDALibraries/simpleCUFFT. Some can be compiled but not executed like 7_CUDALibraries/cuSolverSp_LinearSolver

CUDA error at cuSolverSp_LinearSolver.cpp:278 code=1(CUSPARSE_STATUS_NOT_INITIALIZED) “cusparseCreate(&cusparseHandle)”

, and some can’t be compiled like 7_CUDALibraries/conjugateGradient. Does it mean CUDA is actually set up? Since PyTorch is nothing different from these CUDA samples in terms of calling CUDA interface, if all CUDA APIs PyTorch is calling are those in samples that I can compile and execute, PyTorch should be good to run. But why can’t PyTorch find any GPU? Is it possible I install a PyTorch in my user space (or build up one from source) and this PyTorch version can see the GPU?