论文标题

概率值探测与源源相关的位级通道适应以进行近似通信

Probabilistic Value-Deviation-Bounded Source-Dependent Bit-Level Channel Adaptation for Approximate Communication

论文作者

Bilgin, Bilgesu Arif, Stanley-Marbell, Phillip

论文摘要

可以忍受其通信数据值效果的计算系统可以将这种容忍度交换以提高资源效率。计算的许多重要应用,例如嵌入式传感器系统,可以忍受其与正确性(失真)偏差分布的误差。我们提出了一种通道适应技术,该技术调节了嵌入式传感器系统中典型的I/O通道的属性,以在I/O功率耗散和通信数据的变形之间进行权衡。我们为分布传输值的分布提供了有效的计算公式。使用此公式,我们实施了我们的价值传播(VDB)通道适应。我们通过实验量化与所需的可编程通道调制电路集成的硬件原型上的功率耗散减少。我们通过分析扭曲的分布来增强这些实验测量。我们表明,我们的概率VDB频道改编可提供高达2 $ \ times $减少I/O功率耗散。当合成用于传感器界面的微型低功率FPGA时,通道自适应控制逻辑的寄存器传输级别实现仅需要106个触发器和224个4输入LUTS,即可在8位传感器数据的序列化流中实现每位通道自适应。

Computing systems that can tolerate effects of errors in their communicated data values can trade this tolerance for improved resource efficiency. Many important applications of computing, such as embedded sensor systems, can tolerate errors that are bounded in their distribution of deviation from correctness (distortion). We present a channel adaptation technique which modulates properties of I/O channels typical in embedded sensor systems, to provide a tradeoff between I/O power dissipation and distortion of communicated data. We provide an efficient-to-compute formulation for the distribution of integer distortion accounting for the distribution of transmitted values. Using this formulation we implement our value-deviation-bounded (VDB) channel adaptation. We experimentally quantify the achieved reduction in power dissipation on a hardware prototype integrated with the required programmable channel modulation circuitry. We augment these experimental measurements with an analysis of the distributions of distortions. We show that our probabilistic VDB channel adaptation can provide up to a 2$\times$ reduction in I/O power dissipation. When synthesized for a miniature low-power FPGA intended for use in sensor interfaces, a register transfer level implementation of the channel adaptation control logic requires only 106 flip-flops and 224 4-input LUTs for implementing per-bit channel adaptation on serialized streams of 8-bit sensor data.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源