Bazel-buildfarm-指定worker的并发 [英] Bazel-buildfarm - specifying concurrency of worker
问题描述
我正在尝试使用bazel-buildfarm构建TensorFlow.我有一个服务器和一个单一的工作程序设置，使用的配置示例位于 https://github.com/bazelbuild/bazel-buildfarm (请参见examples/目录).唯一的工人在72核计算机上.
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.
我遇到的问题是，一旦启动构建，尽管构建目标已成功分发给工作人员，但工作人员并未利用我的所有核心(甚至没有关闭).我尝试在启动TensorFlow构建时在客户端上显式设置--jobs=100，但无济于事.
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.
有人知道我如何让我的单身工人充分利用可用的处理能力吗?是否需要在工作程序配置文件中明确指定?
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?
推荐答案
工作程序配置文件具有名为execute_stage_width的设置，可用于指定并发程度.
The worker configuration file has a setting called execute_stage_width which can be used to specify degree of concurrency.
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