device management==================FLAGS_paddle_num_threads*******************************************(since 0.15.0)Control the number of threads of each paddle instance.Values accepted---------------Int32. The default value is 1.Example-------FLAGS_paddle_num_threads=2 will enable 2 threads as max number of threads for each instance.FLAGS_selected_gpus*******************************************(since 1.3)Set the GPU devices used for training or inference.Values accepted---------------A comma-separated list of device IDs, where each device ID is a nonnegative integer less than the number of GPU devices your machine have.Example-------FLAGS_selected_gpus=0,1,2,3,4,5,6,7 makes GPU devices 0-7 to be used for training or inference.Note-------The reason for using this flag is that we want to use collective communication between GPU devices, but with CUDA_VISIBLE_DEVICES can only use share-memory.
