SHF: Small: Digital Signal Processing using Stochastic Computing

SHF：小型：使用随机计算的数字信号处理

• 批准号: 1319107
• 负责人: Keshab Parhi
• 金额: $ 37.5万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-15 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1319107&HistoricalAwards=false
• 关键词: SHF; Small; Digital; Signal; Processing

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.

随机计算是二进制计算的一种替代方法，它具有固有的容错性。一个数字被概率性地编码为N比特流中1的数量。数字的随机表示是高度冗余的，这转化为容错。在许多应用中，计算的精确性不太重要，随机计算可能是一个理想的选择。其缺点包括更长的延迟和存储需求的数量级增加。然而，在非常需要容错的深亚微米技术中，随机计算方法可以提供某些优点。很少有人了解使用随机计算实现的数字信号处理（DSP）算法的性能。这个项目将试图了解如何使用随机计算实现各种DSP功能。努力将针对理解的特点，如容错性，有限精度的影响，两个互补随机数转换等视频编码中的应用将被探索，以证明数字信号处理应用的随机计算方法的实用性。这种方法如果被证明是成功的，可能在许多需要容错的应用中是有用的，但可以容忍一些错误。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课程项目培养研究生。研究生将把技术转移到工业领域。将招募妇女和少数民族参加该项目。该项目的成果将通过期刊和会议上的出版物以及PI在半导体行业的讲座进行传播。