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python - Does TensorFlow view all CPUs of one machine as ONE device?

From the experiments I run, it seems like TensorFlow uses automatically all CPUs on one machine. Furthermore, it seems like TensorFlow refers to all CPUs as /cpu:0.

Am I right, that only the different GPUs of one machine get indexed and viewed as separate devices, but all the CPUs on one machine get viewed as a single device?

Is there any way that a machine can have multiple CPUs viewing it from TensorFlows perspective?

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By default all CPUs available to the process are aggregated under cpu:0 device.

There's answer by mrry here showing how to create logical devices like /cpu:1, /cpu:2

There doesn't seem to be working functionality to pin logical devices to specific physical cores or be able to use NUMA nodes in tensorflow.

A possible work-around is to use distributed TensorFlow with multiple processes on one machine and use taskset on Linux to pin specific processes to specific cores


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