############################################################################### Compile FSL -- Getting a docker env for compiling FSL with GCC 4.8 ubuntu 19.04 ############################################################################### ********** Get Set up ********** Install cuda, nvidia-docker2 I am following along on this series, except installing onto a Ubuntu 19.04 and cuda 10.1 setup https://www.pugetsystems.com/labs/hpc/How-To-Install-CUDA-10-1-on-Ubuntu-19-04-1405/ Has links to the previous 4 posts as well: https://www.pugetsystems.com/labs/hpc/How-To-Setup-NVIDIA-Docker-and-NGC-Registry-on-your-Workstation---Part-5-Docker-Performance-and-Resource-Tuning-1119/ https://devblogs.nvidia.com/gpu-containers-runtime/ Create container I installed using the 18.04 apt source (bionic) as docker-ce does not exist for the 19.04 variant (disco), and the latest variant nvidia supports for the nvidia-docker2 is 18.04 https://docs.docker.com/install/linux/docker-ce/ubuntu/ I did the post install steps to allow non-privileged users access to docker commands https://docs.docker.com/install/linux/linux-postinstall/ On to nvidia-docker I followed this, with the noted exceptions: https://devblogs.nvidia.com/gpu-containers-runtime/ I added the 18.04 package list, as 19.04 isn't supported. In the pugetsystems install cuda 10.1 reference he says he did this without issue.:: curl -s -L https://nvidia.github.io/nvidia-docker/ubuntu18.04/nvidia-docker.list | \ sudo tee /etc/apt/sources.list.d/nvidia-docker.list I ran through the nvidia docker tests and it seemed to work. great! User namespaces following along: https://www.pugetsystems.com/labs/hpc/How-To-Setup-NVIDIA-Docker-and-NGC-Registry-on-your-Workstation---Part-3-Setup-User-Namespaces-1114/ Having issues with network connectivity? Check out this superuser post https://superuser.com/questions/1130898/no-internet-connection-inside-docker-containers/1335054#1335054 ************** FSL Dockerfile ************** Need: gcc4.8, and cuda 10.1 container So: https://gitlab.com/nvidia/cuda, then install gcc4.8 and change the gcc links Then: open fsl source Then: run build succcessfully Then: expose a job to go to our pipeline directory and run the python pipeline script Have FSLDIR and FSL_DIR mapped in the env nvidia's available base container Dockerfile definitions are [available here](https://gitlab.com/nvidia/cuda/tree/ubuntu16.04/10.1). There's a branch for each ubuntu release they support. *************** The actual file *************** .. include:: fsl_env_dockerfile :code: bash