Probabilistic Value-Deviation-Bounded Source-Dependent Bit-Level Channel Adaptation for Approximate Communication
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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 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
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1557-9956
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Royal Society (RG170136)