NANO: Information-Theoretic Foundation of Molecular Computing: Performance Limits and Design Optimization

NANO：分子计算的信息理论基础：性能限制和设计优化

• 批准号: 0621947
• 负责人: Lei Wang
• 金额: $ 27.5万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0621947&HistoricalAwards=false
• 关键词: NANO; Information; Theoretic; Foundation; Molecular

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.

分子计算试图通过探索纳米级组件之间的信息处理机制来推动新的计算范例。最终系统将是超密集，超快速且能够执行可能带来直觉，创造力，效率和其他生物生物基本特性的计算任务的平台。预计这些未来的计算系统将通过使用生物编码的遗传材料（DNA计算）或纳米级设备（例如量子点设备，碳纳米管和纳米线（纳米电计算））来构建。与传统的计算系统不同，分子计算具有一些独特的特征，例如随机和不完美的分子相互作用，固有的冗余促进大规模并行性以及分布式阵列结构，促进了广泛的分子加工核心的合作。这项研究旨在建立信息理论基础，以揭示分子计算中基本挑战的关键性质和实际意义。该项目的目标是（1）开发用于分子计算的信息理论模型； （2）使用信息理论分析确定分子计算的基本性能限制； （3）探索新的分子计算解决方案，这些解决方案允许冗余性能驱动的任务和可靠性驱动的任务的动态分布，从而将性能推向基本限制； （4）开发纳米电路和纳米级集成方案，这些方案结合了信息理论的见解和物理设计技术，以实现新的信息处理边界。综合教育部分的目标是（1）解决计算机工程中劳动力培训的更广泛需求，尤其是分子计算的新兴技术； （2）促进研究生和本科生广泛参与分子计算的新思想； （3）在研究社区，少数群体和公众之间传播新的研究结果。