Toward Energy-Efficient, Bio-Inspired Circuits and Systems for Error-Resilient and Biomedical Applications

面向防错和生物医学应用的节能、仿生电路和系统

• 批准号: RGPIN-2015-06007
• 负责人: Han, Jie
• 金额: $ 1.82万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=681240
• 关键词: Toward; Energy; Efficient; Bio; Inspired

Many of us get our computers, laptops or phones replaced every few years. Technology advances due to the continuous miniaturization of electronic devices, such that a larger number of devices can be packed into a single chip, while the cost has been kept relatively stable. This trend has slowed down, however, and is predicted to end in less than a decade. A transistor, the basic functional unit in a circuit, is now sized in just a few nanometers, that is, a few billionth of a meter. At such a small scale, it is difficult to fabricate all transistors uniformly and make them operate reliably. The current method to ensure a reliable operation is to apply a larger power than it is often necessary, so electronics still consume a lot of energy. On the other hand, many computer applications, such as multimedia, voice recognition and web search, do not always require a fully accurate result and a "good-enough" result is often sufficient due to many factors such as human perceptual limitations. This class of applications is considered imprecision-tolerant or error-resilient. One objective of this research program is to address the energy-efficiency and error-resilience issues in nanometer-scale electronics by developing new and innovative computational structures that employ approximate, stochastic and the brain-inspired neuromorphic computing techniques. These new techniques allow computing systems to trade off quality for energy. ******As a transistor is to a computer, a cell is the basic unit of life in a biological system such as a human body. The advances of computing techniques also provide opportunities to help address some emerging biomedical issues. For example, computational models have been used to help understand how a gene network functions in a cell. Validated computational results provide additional knowledge to our understanding of biological systems. The other objective of this research program is to apply computing techniques to the modeling and analysis of biological networks by exploiting the similarity between an electronic circuit and a biological network. Such a network can be a genetic network or a signaling pathway in a cancerous cell. The obtained results will help to investigate gene intervention-based therapeutic methods for some genetic diseases such as cancer. ******This research program addresses some of the fundamental and challenging issues faced by the information technology industry and the biomedical research community. It will take a truly interdisciplinary approach to leveraging the interactions between computer engineering, computational biology and biomedical engineering. This program will also facilitate the training of highly qualified personnel (HQP) with skills highly demanded by the high-tech sectors in Canadian industry. Such skills will be crucial to the long-term growth of the economy, and thus will be of significant economic importance to Canada.**

我们中的许多人每隔几年就会更换一次电脑、笔记本电脑或手机。由于电子设备的不断小型化，技术进步，使得更大数量的设备可以封装到单个芯片中，而成本保持相对稳定。然而，这一趋势已经放缓，预计将在不到十年的时间内结束。晶体管，电路中的基本功能单元，现在的尺寸只有几纳米，也就是几十亿分之一米。在如此小的规模下，很难均匀地制造所有晶体管并使它们可靠地工作。目前确保可靠运行的方法是施加比通常所需的更大的功率，因此电子设备仍然消耗大量能量。另一方面，许多计算机应用，例如多媒体、语音识别和网络搜索，并不总是需要完全准确的结果，并且由于诸如人类感知限制的许多因素，“足够好”的结果通常是足够的。这类应用程序被认为是不精确的容忍或错误弹性。该研究计划的一个目标是通过开发采用近似、随机和大脑启发的神经形态计算技术的新型创新计算结构来解决纳米级电子产品中的能源效率和错误恢复问题。这些新技术允许计算系统在质量和能量之间进行权衡。****** 就像晶体管之于计算机一样，细胞是生物系统（如人体）中生命的基本单位。计算技术的进步也为帮助解决一些新出现的生物医学问题提供了机会。例如，计算模型已被用于帮助理解基因网络如何在细胞中发挥作用。经过验证的计算结果为我们理解生物系统提供了额外的知识。该研究计划的另一个目标是通过利用电子电路和生物网络之间的相似性，将计算技术应用于生物网络的建模和分析。这种网络可以是癌细胞中的遗传网络或信号通路。本研究结果将有助于探索基于基因干预的癌症等遗传性疾病的治疗方法。* 该研究计划解决了信息技术行业和生物医学研究界面临的一些基本和具有挑战性的问题。它将采取真正的跨学科方法来利用计算机工程，计算生物学和生物医学工程之间的相互作用。该计划还将促进高素质人员（HQP）的培训，这些人员具有加拿大工业高科技部门高度要求的技能。这些技能对经济的长期增长至关重要，因此对加拿大具有重大的经济意义。