Danny Hillis tells us why Computer Science is no good.
longnow.org
longnow.org
Its much more likely to look like biology, eg nature's computers. Most models in physics are not inherently based on the idea of information and computation, in fact the functions that they are based on are merely primitive recursive, making them unsuitable for for descriptions of fully generally recursive computational processes.
Of course, biology is also noted for its lack of higher theory, and so when I make the above claim, the meaning is that when such a theory exists it will address both of these issues.
I hope I'm not the only one who finds this hilarious.
His point, if I'm reading it correctly, is that we treat wires as an ideal and instantaneous transfer medium. In reality, however, wires take up physical space, so there are physical limits to the number and length of wires you can actually have. The more wires you use, the longer they need to be to route around each other, hence more time needed to transfer the data, breaking the abstraction.
Analogously, a memory location ideally represents something you can dump data into at one time, then extract it instantaneously at a later time. In reality, however, processors need to address memory via the bus. With a single bus, processors will have to queue their requests -- resulting in longer "time wires" and a slower computer. The alternative is to have multiple memories/buses (more "time wires"), but since the buses are constrained by physical limits, the number of "time wires" you can have is constrained just like the number of real wires. So our abstraction of memory is broken -- the amount of time it takes to access a memory location depends on how many locations we need.
You can see a similar result in today's machines, in the behavior of cache locality: if your algorithm tries to access too much data (many "time wires"), it overflows the cache and you're forced to wait (use longer "time wires"). Algorithms designed to exploit cache effects are sometimes an order of magnitude faster, illustrating the leakiness of our memory abstraction.
Just to put "recent" into perspective, this article is from 1981 :)
If we are talking about the physical devices that do the computation, it's within the field of Engineering.
Daniel Hillis is an incredibly clever guy and the Connection Machines were probably the most beautiful computers ever built. Not only that, but they were, perhaps, the last computers ever built you could tell what they were doing just by looking at them.
I would love to see something like that on a desktop PC. Maybe not tasks or threads (and, certainly, not processors) or memory blocks being accessed and translating the patterns into blinking lights.
It usually works out that the useless math of one day becomes very useful some later day, usually in an incredibly unexpected way. It is also usual that physicist tend to discover a use well before any engineers start poking around it.
As for observing nature, it's also frequent that engineers find ways to control and use something well before physicists have any clue as to how and why it works.
yawn