首页> 外文会议>IFIP 249; International Conference on Very Large Scale Integration of System on Chip(VLSI-SoC 2006); 20061016-18; Nice(FR) >Probabilistic Design: A Survey of Probabilistic CMOS Technology and Future Directions for Terascale IC Design
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Probabilistic Design: A Survey of Probabilistic CMOS Technology and Future Directions for Terascale IC Design

机译:概率设计:概率CMOS技术的调查以及万亿级IC设计的未来方向

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Highly scaled CMOS devices in the nanoscale regime would inevitably exhibit statistical or probabilistic behavior. Such behavior is caused by process variations, and other perturbations such as noise. Current circuit design methodologies, which depend on the existence of "deterministic" devices that behave consistently in temporal and spatial contexts do not admit considerations for probabilistic behavior. Admittedly, power or energy consumption as well as the associated heat dissipation are proving to be impediments to the continued scaling (down) of device sizes. To help overcome these challenges, we have characterized CMOS devices with probabilistic behavior (probabilistic CMOS or PCMOS devices) at several levels: from foundational principles to analytical modeling, simulation, fabrication, measurement as well as exploration of innovative approaches towards harnessing them through system-on-a-chip architectures. We have shown that such architectures can implement a wide range of probabilistic and cognitive applications. All of these architectures yield significant energy savings by trading probability with which the device operates correctly-lower the probability of correctness, the greater the energy savings. In addition to these PCMOS based innovations, we will also survey probabilistic arithmetic-a novel framework through which traditional computing units such as adders and multipliers can be deliberately designed to be erroneous, while being characterized by a well-defined probability of correctness. We demonstrate that in return for erroneous behavior, significant energy and performance gains can be realized through probabilistic arithmetic (units)-over a factor of 4.62X in the context of an FIR filter used in a H.264 video decoding-where the gains are quantified through the energy-performance product (or EPP). These gains are achieved through a systematic probabilistic design methodology enabled by a design space spanning the probability of correctness of the arithmetic units, and their associated energy savings.
机译:纳米尺度的大规模CMOS器件将不可避免地表现出统计或概率行为。这种行为是由过程变化和其他干扰(例如噪声)引起的。当前的电路设计方法依赖于在时间和空间环境中始终如一地运行的“确定性”设备的存在,因此不考虑概率行为。公认的是,功率或能量消耗以及相关的散热被证明阻碍了器件尺寸的持续缩小(缩小)。为帮助克服这些挑战,我们在几个级别上对具有概率行为的CMOS设备(概率CMOS或PCMOS器件)进行了特征化:从基本原理到分析建模,仿真,制造,测量,以及探索通过系统利用它们的创新方法,片上架构。我们已经证明,这样的体系结构可以实现各种概率和认知应用。所有这些架构都可以通过权衡设备正确运行的概率来节省大量能源,正确率越低,则节省的能量就越大。除了这些基于PCMOS的创新之外,我们还将研究概率算术-一种新颖的框架,通过该框架,可以故意将传统的计算单元(如加法器和乘法器)设计为错误的,同时具有明确定义的正确性概率。我们证明,作为错误行为的回报,可以通过概率算术(单位)在H.264视频解码中使用的FIR滤波器的情况下,通过概率算法(单位)实现4.62倍的显着能量和性能提升,其中通过能源绩效产品(或EPP)进行量化。这些收益是通过系统的概率设计方法来实现的,该方法由跨越算术单元正确性及其相关能量节省的可能性的设计空间实现。

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