Approaching the Physical Limits of Computing

and long-standing relation. Scientific and engineering problems tend to place some of the most demanding requirements on computational power, thereby driving the engineering of new bit-device technologies and circuit architectures, as well as the scientific & mathematical study of better algorithms and more sophisticated computing theory. The need for finite-difference artillery ballistics simulations during World War II motivated the ENIAC, and massive calculations in every area of science & engineering motivate the PetaFLOPS-scale * supercomputers on today’s drawing boards (cf. IBM’s Blue Gene [1]). Meanwhile, computational methods themselves help us to build more efficient computing systems. Computational modeling and simulation of manufacturing processes, logic device physics, circuits, CPU architectures, communications networks, and distributed systems all further the advancement of computing technology, together achieving ever-higher densities of useful computational work that can be performed using a given quantity of time, material, space, energy, and cost. Furthermore, the long-term economic growth enabled by scientific & engineering advances across many fields help