Molecular computing seeks to advance new computing paradigms by exploring information processing mechanisms among nanoscale components. The ultimate systems will be the platforms that are ultra-dense, ultra-fast, and capable of performing computational tasks that may bring intuition, creativity, efficiency, and other essential properties of living organisms. These future computing systems are expected to be constructed via bottom-up self-assembly using biologically encoded genetic materials (DNA computing) or nanoscale devices such as quantum-dot devices, carbon nanotubes and nanowires (nanoelectronic computing). Unlike conventional computing systems, molecular computing has some unique features such as random and imperfect molecular interactions, inherent redundancy facilitating massive parallelism, and distributed array architecture promoting cooperation among vast molecular processing cores. This research seeks to develop an information-theoretic foundation to reveal the key nature and practical implications of the fundamental challenges in molecular computing. The goals of this project are to (1) develop an information-theoretic model for molecular computing; (2) determine the fundamental performance limits of molecular computing using information-theoretic analysis; (3) explore new molecular computing solutions that allow dynamic distribution of redundant performance-driven tasks and reliability-driven tasks, thereby pushing the performance towards the fundamental limits; and (4) develop nanocircuits and nanoscale integration schemes that incorporate information-theoretic insights and physical design techniques for new frontiers of information processing. The goals of the integrated education component are to (1) address the broader need of workforce training in computer engineering, in particular, the emerging technology of molecular computing; (2) foster extensive involvement of graduate and undergraduate students in the exploration of new ideas of molecular computing; and (3) disseminate new research findings among research communities, minority groups, and general public.
NANO: Information-Theoretic Foundation of Molecular Computing: Performance Limits and Design Optimization