Make it possible for generators to simulate combinatorial logic

[nakengelhardt]

Sometimes I want to use generators to build a simulation model of some module. In migen, this wasn't possible for modules that implement combinatorial logic.

Trying my hand at nmigen syntax, an example could be something like this:

class RoutingPolicy:
    def __init__(self, width, n):
        self.data = Signal(width)
        self.destination = Signal(max=n)

    # I haven't decided yet what I want this module to do, let's try some options
    def gen_destination(self):
        while True: # or something?
            data = (yield self.data)
            if (data == 23):
                yield self.destination.eq(0)
            else:
                yield self.destination.eq(self.data[:log2_int(n)])

class Router:
    def __init__(self, width, n):
        self.in_port = Signal(width)
        self.out_ports = Array(Signal(width) for _ in range(n))

        self.policy = RoutingPolicy(width, n)

    def get_fragment(self, platform):
        m = Module()
        m.submodules.policy = self.policy
        m.d.comb += [
            self.policy.data.eq(self.in_port),
            self.out_ports[self.policy.destination].eq(self.in_port)
        ]
        return m.lower(platform)

m = Router(8, 2)
run_simulation(m, m.policy.gen_destination())

There probably needs to be something to tell what constitutes one iteration of the generator, with while True it would just run indefinitely. while (yield input_values_changed()): ? Also the whole thing would need to be @passive or so since there's no predefined end point. Another question is whether it's possible, or even makes sense, to mix combinatorial assignments and synchronous assignments in one generator.