SHF: Small: Digital Signal Processing using Stochastic Computing

随机计算是二进制计算的一种替代方案，具有固有的容错能力。数字被概率地编码为N比特流中的1的个数。数字的随机表示是高度冗余的，这转化为容错。在计算精确度不那么重要的许多应用中，随机计算可能是理想的替代方案。它的缺点包括更长的等待时间和存储需求的数量级增长。然而，在高度需要容错的深亚微米技术中，随机计算方法可能会提供一定的优势。人们对使用随机计算实现的数字信号处理(DSP)算法的性能了解很少。本项目将尝试了解如何使用随机计算来实现各种DSP功能。将致力于了解诸如容错、有限精度效应、二的补码到随机数的转换等特性。将探索在视频编码中的应用，以展示随机计算方法在数字信号处理应用中的实用性。这种方法如果被证明是成功的，在许多需要容错的应用程序中可能很有用，但可以容忍一些错误。然后，这项研究的影响可以转化为半导体行业的新产品和新市场。拟议的研究将通过相关的课程项目来培养研究生。研究生将把技术转移到行业。将招募妇女和少数民族参加这一项目。该项目的结果将通过期刊和会议上的出版物以及半导体行业国际协会的演讲来传播。

Stochastic computing is an alternative to binary computing that is inherently fault tolerant. A number is encoded probabilistically as the number of 1s in a stream of N bits. Stochastic representation of numbers is highly redundant, which translates to fault tolerance. In many applications where exactness of computations is less important, stochastic computing may be a desired alternative. Its drawbacks include longer latency and orders of magnitude increase in storage requirements. Nevertheless, in deep submicron technology where fault tolerance is highly desirable, the stochastic computing approach may provide certain advantages. Very little is understood about the performance of Digital Signal Processing (DSP) algorithms implemented using stochastic computing. This project will attempt to understand how various DSP functions can be implemented using stochastic computing. Efforts will be directed towards understanding characteristics such as fault-tolerance, finite precision effects, conversion of two's complement to stochastic numbers, etc. Applications in video coding will be explored to demonstrate the utility of the stochastic computing approach for digital signal processing applications. The approach, if proven successful, may be useful in many applications that require fault tolerance, but can tolerate some error. The impact of the research could then be translated to new products and new markets in the semiconductor industry. The proposed research will train graduate students through related course projects. Graduate research students will transfer technology to industries. Women and minorities will be recruited to participate in this project. Results of the project will be disseminated through publications in journals and conferences, and by talks by the PI in semiconductor industries.