When I try to profile the memory usage of model training in TensorFlow, I found there are two relevant information collected by TensorFlow Timeline tool, GPU_0_bfc and GPU_host_bfc (see the following figure), I am wondering which one can reflect the most accurate memory usage? or What is the difference between them? Thanks.
Difference between GPU_0_bfc allocator and GPU_host_bfc allocoator in TensorFlow Timeline
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1 Answers
It seems that GPU_host_bfc is the usage of the allocated memory on the host (e.g. the RAM next to the CPU). This is usually less than the physically (and/or through swap) available memory.
Further reading here.
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