The CPU backend as it is today (and what I perceive its intent to be) is to support running the network on a (single-core) CPU (X86, ARM, etc.).

That is correct.
That said, we are looking into adding support for partitioning the input across device.
See:

  
      github.com/pytorch/glow
  
  
    



Issue: Graph partitioning for multi-device execution 55


	
	opened by bertmaher
	on 2018-07-12
	
	
	


Partitioning a Function into multiple subgraphs breaks a lot of assumptions in our current architecture. PR #1176 shows a proof-of-concept for...