I am trying to build TensorFlow using bazel-buildfarm. I have a server and a single worker setup using the example configurations available at https://github.com/bazelbuild/bazel-buildfarm (see examples/ directory). The lone worker is on a 72-core machine.
The problem I'm having is that once I kick off a build, although the build targets are being successfully dispatched to the worker, the worker is not taking advantage of all my cores (not even close). I tried explicitly setting --jobs=100 on the client when I initiate the TensorFlow build, but to no avail.
Does anyone have an idea how I can get my single worker to fully utilize the processing power available to it? Does this need to be specified explicitly in a worker configuration file?
The worker configuration file has a setting called execute_stage_width which can be used to specify degree of concurrency.