Project 3 components, up to RAM64

[mossprescott]

• Add clock as a special signal, available to all components, with operations tick() and tock() to update it and propagate state
• Add lazy() creating forward references when building components, so that circular references can be created
• Correct the topological ordering of nodes so that updates are actually stable
• Fix sorted_nodes to not be O(n^2) so it all actually works
• Add a hack to capture the name of the builder function and label each node in the mapping of internal states with it, so there's some hope of figuring out what's what
• Keep track of the mapping of internal nodes to bits in the vector, and expose it via internal()

With all that, DFF can be implemented from nands, and the components of project #3 can be implemented on top of that.

A simple test for each RAM is here; I didn't try to translate the original test suite, which is getting tedious. Nevertheless, the tests could be stronger.

Currently the compiler is taking ~25 seconds to translate RAM64 into the bit vector representation. After that, individual operations are reasonably fast (~50ms per clock), even though each step is now copying a vector of about 17k bits. This clearly isn't going to scale to larger memories, so a new approach will be needed to get further.

cc @dfithian

[dfithian]

When you say "compiler" do you mean Python interpreter or combination of Python interpreter + underlying Python code you wrote here?

[mossprescott]

The "compiler" is the code in compiler.py that translates a graph of components into the new NandVector representation which is efficient to evaluate.

That code is very clearly the bottleneck at this point. I have a couple of ideas for making it better, and hopefully one of them pans out because at this point a 64-word memory is slightly beyond the limit of usability.