Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Invocation-driven Neural Approximate Computing with a
  Multiclass-Classifier and Multiple Approximators   Neural approximate computing gains enormous energy-efficiency at the cost of
tolerable quality-loss. A neural approximator can map the input data to output
while a classifier determines whether the input data are safe to approximate
with quality guarantee. However, existing works cannot maximize the invocation
of the approximator, resulting in limited speedup and energy saving. By
exploring the mapping space of those target functions, in this paper, we
observe a nonuniform distribution of the approximation error incurred by the
same approximator. We thus propose a novel approximate computing architecture
with a Multiclass-Classifier and Multiple Approximators (MCMA). These
approximators have identical network topologies and thus can share the same
hardware resource in a neural processing unit(NPU) clip. In the runtime, MCMA
can swap in the invoked approximator by merely shipping the synapse weights
from the on-chip memory to the buffers near MAC within a cycle. We also propose
efficient co-training methods for such MCMA architecture. Experimental results
show a more substantial invocation of MCMA as well as the gain of
energy-efficiency.

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The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
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The categories of this paper are: physics
11
The categories of this paper are: hep-lat
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The categories of this paper are: q-bio
22
The categories of this paper are: chao-dyn
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The categories of this paper are: alg-geom
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The categories of this paper are: astro-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: eess