用于随机计算的相关操作电路

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摘要翻译：
随机计算(SC)是一种新兴的计算技术，具有高密度、低功耗、容错等优点。在SC中，值被编码为一元比特流，并且SC算术电路对一个或多个比特流进行操作。在许多情况下，输入比特流必须是相关的或不相关的，SC算法才能产生准确的结果。因此，设计SC加速器的一个关键挑战是操纵跨SC操作的相关性的影响。本文提出并评价了一组用于管理SC计算中相关的新型相关操作电路：同步器、去同步器和去相关器。然后我们利用这些电路提出改进的SC最大、最小和饱和加法器设计。与现有的相关操作技术相比，我们的电路具有更高的精度和高达3倍的能量效率。在图像处理流水线的上下文中，这些电路可以降低高达24%的总能耗。
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英文标题：
《Correlation Manipulating Circuits for Stochastic Computing》
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作者：
Vincent T. Lee, Armin Alaghi, Luis Ceze
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Computer Science        计算机科学
二级分类：Hardware Architecture        硬件体系结构
分类描述：Covers systems organization and hardware architecture. Roughly includes material in ACM Subject Classes C.0, C.1, and C.5.
涵盖系统组织和硬件架构。大致包括ACM主题课程C.0、C.1和C.5中的材料。
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英文摘要：
  Stochastic computing (SC) is an emerging computing technique that promises high density, low power, and error tolerant solutions. In SC, values are encoded as unary bitstreams and SC arithmetic circuits operate on one or more bitstreams. In many cases, the input bitstreams must be correlated or uncorrelated for SC arithmetic to produce accurate results. As a result, a key challenge for designing SC accelerators is manipulating the impact of correlation across SC operations. This paper presents and evaluates a set of novel correlation manipulating circuits to manage correlation in SC computation: a synchronizer, desynchronizer, and decorrelator. We then use these circuits to propose improved SC maximum, minimum, and saturating adder designs. Compared to existing correlation manipulation techniques, our circuits are more accurate and up to 3x more energy efficient. In the context of an image processing pipeline, these circuits can reduce the total energy consumption by up to 24%.
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PDF链接：
https://arxiv.org/pdf/1803.04862

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关键词：随机计算 manipulating Applications Architecture Optimization 电路 挑战 加速器 more 效率