Probabilistic Value-Deviation-Bounded Source-Dependent Bit-Level Channel Adaptation for Approximate Communication
Bilgesu Arif Bilgin, Phillip Stanley-Marbell

TL;DR
This paper introduces a probabilistic channel adaptation method that bounds data deviation, reducing I/O power dissipation by up to 2 times in embedded sensor systems while maintaining acceptable error levels.
Contribution
It presents a novel value-deviation-bounded (VDB) channel adaptation technique with an efficient formulation for integer distortion distribution, enabling power-efficient approximate communication.
Findings
Achieves up to 2× reduction in I/O power dissipation.
Provides a hardware-efficient implementation requiring minimal FPGA resources.
Validates power savings through experimental measurements on a prototype.
Abstract
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…
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