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In this review, we will discuss a possible roadmap in scaling a nanoelectronic device from today's CMOS technology to the ultimate limit when the device fails. In other words, at the limit, CMOS will have a severe short channel effect, significant power dissipation in its quiescent (standby) state, and problems related to other essential characteristics. Efforts to use structures such as the double gate, vertical surround gate, and SOI to improve the gate control have continually been made. Other types of structures using SiGe source/drain, asymmetric Schottky source/drain, and the like will be investigated as viable structures to achieve ultimate CMOS. In reaching its scaling limit, tunneling will be an issue for CMOS. The tunneling current through the gate oxide and between the source and drain will limit the device operation. When tunneling becomes significant, circuits may incorporate tunneling devices with CMOS to further increase the functionality per device count. We will discuss both the top-down and bottom-up approaches in attaining the nanometer scale and eventually the atomic scale. Self-assembly is used as a bottom-up approach. The state of the art is reviewed, and the challenges of the multiple-step processing in using the self-assembly approach are outlined. Another facet of the scaling trend is to decrease the number of electrons in devices, ultimately leading to single electrons. If the size of a single-electron device is scaled in such a way that the Coulomb self-energy is higher than the thermal energy (at room temperature), a single-electron device will be able to operate at room temperature. In principle, the speed of the device will be fast as long as the capacitance of the load is also scaled accordingly. The single-electron device will have a small drive current, and thus the load capacitance, including those of interconnects and fanouts, must be small to achieve a reasonable speed. However, because the increase in the density (and/or functionality) of integrated circuits is the principal driver, the wiring or interconnects will increase and become the bottleneck for the design of future high-density and high-functionality circuits, particularly for single-electron devices. Furthermore, the massive interconnects needed in the architecture used today will result in an increase in load capacitance. Thus for single-electron device circuits, it is critical to have minimal interconnect loads. And new types of architectures with minimal numbers of global interconnects will be needed. Cellular automata, which need only nearest-neighbor interconnects, are discussed as a plausible example. Other architectures such as neural networks are also possible. Examples of signal processing using cellular automata are discussed. Quantum computing and information processing are based on quantum mechanical descriptions of individual particles correlated among each other. A quantum bit or qubit is described as a linear superposition of the wave functions of a two-state system, for example, the spin of a particle. With the interaction of two qubits, they are connected in a "wireless fashion" using wave functions via quantum mechanical interaction, referred to as entanglement. The interconnection by the nonlocality of wave functions affords a massive parallel nature for computing or so-called quantum parallelism. We will describe the potential and solid-state implementations of quantum computing and information, using electron spin and/or nuclear spin in Si and Ge. Group IV elements have a long coherent time and other advantages. The example of using SiGe for g factor engineering will be described.