SHF: Small: Stochastic Computing Techniques for Real-Time Image-Processing Applications

计算机的许多有益应用现在不能实现，因为它们需要过高的性能和/或低功率。一个有趣的例子是实时图像处理，以恢复视力受损的人的视力。这个项目探索了一种称为随机计算(SC)的非常规且鲜为人知的技术，它非常适合于这种应用。随机计算以比特流的形式处理数字，这种形式类似于神经信号，并被解释为概率。它可以用小的逻辑电路实现复杂的算术运算。然而，高精度可能需要较长的比特流，这可能难以与传统的二进制逻辑接口。该项目旨在发展SC的全面理论，从而形成设计和应用随机电路的实用方法。它将研究SC的基础，特别是速度、精度和硬件成本之间的权衡，使用各种新方法。随机计算将应用于广泛的图像处理任务，从盲人视网膜植入到即时特征提取。原型设计将通过现场可编程门阵列使用软件模拟和硬件模拟来构建和评估。该项目的目标是在新兴集成电路技术和应用的背景下全面了解随机计算的理论和实践。它的结果应该会引起学术界以及微电子、计算机和生物工程行业的研究工程师和科学家的兴趣。它们还应该对图像处理芯片、植入式医疗设备和视频监控系统等应用领域的设计师和制造商具有直接的实用价值。该项目的成果将主要通过同行评议的期刊和会议论文分发。一个关键的目标是支持计算机科学和工程方面的研究生的培训，这些研究生将直接参与密歇根大学的硕士和博士项目的研究。一些本科生也将被邀请作为实习生加入该项目，以鼓励他们从事与研究相关的职业。将特别努力让妇女和少数族裔学生参与进来。

Many beneficial applications of computers cannot now be realized because they demand excessively high performance and/or low power. An example of interest is real-time image processing to restore sight to the visually impaired. This project explores an unconventional and little-understood technology called stochastic computing (SC) which is very well-suited to such applications. Stochastic Computing processes numbers in the form of bit-streams that resemble neural signals and are interpreted as probabilities. It can implement complex arithmetic operations by small logic circuits. However, high accuracy may require long bit-streams that can be difficult to interface with conventional binary logic. The project aims to develop a comprehensive theory of SC leading to practical methods for designing and applying stochastic circuits. It will study the foundations of SC, especially speed, accuracy and hardware-cost trade-offs, using various novel methods. Stochastic Computing will be applied to a broad set of image-processing tasks, ranging from retinal implants for the blind, to on-the-fly feature extraction. Prototype designs will be constructed and evaluated using software simulation and hardware emulation via field-programmable gate arrays. The project's goal is a full theoretical and practical understanding of stochastic computing in the context of emerging integrated circuit technologies and applications. Its results should interest research engineers and scientists in academe, as well as in the microelectronics, computer, and bioengineering industries. They should also be of direct practical value to designers and manufacturers in such application areas as image-processing chips, implantable medical devices, and video surveillance systems. The project's outputs will be distributed primarily via peer-reviewed journal and conference papers. A key goal is to support the training of graduate students in computer science and engineering, who will participate directly in the research as part of their M.S. and Ph.D. programs at the University of Michigan. A few undergraduates will also be invited to join the project as interns to encourage them to pursue research-related careers. A special effort will be made to involve women and minority students.