In general in pytorch, multiple backward pass cannot run concurrently in different threads so there is no benefit in adding such functionality 
We are starting working on this but this is quite tricky as it have very deep implications on how the low level engine behaves.
More generally, pytorch is not great for small workloads at the moment as the overhead of the framework is non negligible in eager mode. But we are working on it