This repository is for platform-specific networking extensions to core TensorFlow and related utilities (e.g. testing).

The design goal is to work towards separately compilable plugins, but initially we'll just be porting the networking related contrib directories since TensorFlow 2.0 will be dropping contrib.

Currently support building GDR, VERBS, and MPI extensions:

Using Bazel:

bazel build -c opt //tensorflow_networking/gdr:gdr_server_lib

Using Docker:

docker build -t tf_networking -f tensorflow_networking/gdr/Dockerfile .

Using Bazel:

bazel build -c opt //tensorflow_networking/verbs:verbs_server_lib

Using Docker:

docker build -t tf_networking -f tensorflow_networking/verbs/Dockerfile .

For the MPI extensions the location to the MPI library has to be configured. The configure script is used to setup this configuration. The script will attempt to find the location of the mpirun binary and from there deduce the include and library paths. You can use the MPI_HOME environment variable if mpirun is not installed in your PATH or you want to use another base path for the MPI library. The configure script will create symbolic links inside the third_party/mpi folder to the relevant MPI header and library files. Furthermore the script will determine if your MPI installation is based on OpenMPI or on MPICH and sets this in the .tf_networking_configure.bazelrc file.

Using Bazel:

By manually answering the relevant configuration questions

./configure
bazel build -c opt //tensorflow_networking/mpi:mpi_server_lib

or by preset answers to the configuration questions

MPI_HOME=<path to mpi folder root> TF_NEED_MPI=1 ./configure
bazel build -c opt //tensorflow_networking/mpi:mpi_server_lib

Using Docker:

docker build -t tf_networking -f tensorflow_networking/mpi/Dockerfile .

Using Bazel:

By manually answering the relevant configuration questions

./configure
bazel build -c opt //tensorflow_networking/mpi_collectives:all

Using Docker:

docker build -t tf_networking -f tensorflow_networking/mpi_collectives/Dockerfile .

Using Bazel:

bazel build -c opt --copt='-std=gnu++14' //tensorflow_networking:libtensorflow_networking.so