Computing 10,000x More Efficiently (slides)
Scaled integers give you an instant and very significant boost in performance.  And, what's best, in most cases the error is far smaller than 1%.  I've done tons of real-time image processing work on FPGA's where you almost never use floating point hardware due to how resource intensive (and slow) it is.<p>Another construct that is extremely fast, cheap and can even represent nonlinear and discontinous relationships is the good-old lookup table.  In hardware (FPGA) you get one result per clock cycle.<p>Now, of course, if you can deal with the error and name the tune with just a handful of transistors it could be a good tool to have.<p>It might make more sense to have a hybrid.  Build a CPU that includes a traditional FPU as well as a "physics-based" FPU.  Then the programmer can decide which way to go by trading off between accuracy and deterministic behavior against speed and errors.