摘要翻译：
物联网（IoT）利用无处不在的互联网连接，将日常物理对象组成一个网络，以实现自动化、远程数据传感和集中管理/控制。IoT对象需要嵌入处理能力来实现这些服务。物联网对象处理单元的设计受到性能、功耗、散热等各种严格要求的制约，为了满足这些不同的要求，需要相应地调整大量的处理器设计参数。在本文中，我们提出了一种时间有效的设计空间探索方法，以确定功率和性能优化的微体系结构配置。我们还讨论了这些微架构配置的可能组合，以形成一个有效的两层异构IoT应用处理器。我们使用一个周期精确模拟器(ESESC)和一组标准的PARSEC和SPLASH2基准来评估我们的设计空间探索方法。结果表明，我们的方法只在3%-5%的设计空间内确定了2.23%-3.69%的微体系结构配置。我们的方法在设计空间探索方面平均达到24.16倍的加速比，而在为处理器寻找功率和性能优化的微架构配置方面则是完全穷尽的探索。
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英文标题：
《Selecting Microarchitecture Configuration of Processors for Internet of
  Things》
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作者：
Prasanna Kansakar and Arslan Munir
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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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英文摘要：
  The Internet of Things (IoT) makes use of ubiquitous internet connectivity to form a network of everyday physical objects for purposes of automation, remote data sensing and centralized management/control. IoT objects need to be embedded with processing capabilities to fulfill these services. The design of processing units for IoT objects is constrained by various stringent requirements, such as performance, power, thermal dissipation etc. In order to meet these diverse requirements, a multitude of processor design parameters need to be tuned accordingly. In this paper, we propose a temporally efficient design space exploration methodology which determines power and performance optimized microarchitecture configurations. We also discuss the possible combinations of these microarchitecture configurations to form an effective two-tiered heterogeneous processor for IoT applications. We evaluate our design space exploration methodology using a cycle-accurate simulator (ESESC) and a standard set of PARSEC and SPLASH2 benchmarks. The results show that our methodology determines microarchitecture configurations which are within 2.23%-3.69% of the configurations obtained from fully exhaustive exploration while only exploring 3%-5% of the design space. Our methodology achieves on average 24.16x speedup in design space exploration as compared to fully exhaustive exploration in finding power and performance optimized microarchitecture configurations for processors.
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PDF链接：
https://arxiv.org/pdf/1802.05123