The "Scientific Discovery through Advanced Computing" (SciDAC) initiative is a set of interconnected projects --- science, software development, and research to directed toward the latter --- designed to support simulation, data exploration, and collaboration in many thrust areas of the U.S. Department of Energy, including: climate modeling, fusion energy, chemistry and materials science, astrophysics, and high energy and particle physics.

Optimal complexity solution algorithms, such as multigrid/multilevel preconditio-

ners, keep the time spent in dominant algebraic kernels close to linear as the applications scale on parallel computers. Krylov accelerators and Jacobian-free variants of Newton's method are wrapped outside to deliver robustness in multirate, multiscale coupled systems, which are solved implicitly.

We illustrate with a range of applications in magnetically confined fusion energy, as the fusion community gears up for participation in the International Thermonuclear Experimental Reactor (ITER) consortium.