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

我们中的许多人每隔几年就会更换电脑、笔记本电脑或手机。技术的进步是由于电子设备的不断小型化，使得更多的设备可以被装入单个芯片，而成本一直保持相对稳定。然而，这一趋势已经放缓，预计将在不到十年的时间内结束。一个晶体管，电路的基本功能单元，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需要的更大的功率，因此电子产品仍然消耗大量能量。另一方面，许多计算机应用，如多媒体、语音识别和网络搜索，并不总是要求一个完全准确的结果，由于许多因素，如人类感知的局限性，一个“足够好”的结果往往就足够了。这类应用程序被认为具有不精确容错性或容错性。这个研究项目的一个目标是通过开发新的和创新的计算结构，采用近似的、随机的和受大脑启发的神经形态计算技术，来解决纳米级电子产品的能源效率和错误恢复问题。这些新技术使计算系统能够以质量换取能源。

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.