Multi-chip support, testing, and failure modes

[arvoelke]

Abstracted two different methods of allocating resources to models:

• OneToOne() which is the same method as before (default)
• RoundRobin(n_chips) which cycles through chips per block / input

Ran the entire unit test suite with a manually-overwritten default of allocator=RoundRobin(n_chips=8) (on our local host; not shown) and discovered that all failed tests currently fall into one of two categories:

1. Convolutional weights (pop[16|32]) across chips
2. Use of SNIPS (precompute=False)

Multi-chip support is otherwise working and the user can override / customize the behaviour, with the following notes:

• RoundRobin(n_chips) gives identical behaviour across any number of n_chips between 1 and 8 inclusive (unit-tested).
• Each failure mode currently returns an error (unit-tested).

The current syntax for running a multi-chip simulation of the model is:

from nengo_loihi.hardware.allocators import RoundRobin  # or OneToOne

with Simulator(model, precompute=True,
               hardware_options={'allocator': RoundRobin(n_chips=8)}):
    ...

Todo:

• Is this abstraction okay for now? I realize things may change and so this is just a basic starting point that can be adapted.
• Is this an acceptable level of exposure to the user, even if it might change in the future? Or do we have better ways of exposing advanced configuration? (Resolution: will need to rethink global simulator configuration at the level of Nengo core)
• Are there more appropriate exceptions to raise?

[arvoelke]

Note to self: since this touches the Simulator docstring it is a natural place to simultaneously fix #147.