Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: CNNdroid: GPU-Accelerated Execution of Trained Deep Convolutional Neural
  Networks on Android   Many mobile applications running on smartphones and wearable devices would
potentially benefit from the accuracy and scalability of deep CNN-based machine
learning algorithms. However, performance and energy consumption limitations
make the execution of such computationally intensive algorithms on mobile
devices prohibitive. We present a GPU-accelerated library, dubbed CNNdroid, for
execution of trained deep CNNs on Android-based mobile devices. Empirical
evaluations show that CNNdroid achieves up to 60X speedup and 130X energy
saving on current mobile devices. The CNNdroid open source library is available
for download at https://github.com/ENCP/CNNdroid

8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
13
The categories of this paper are: quant-ph
18
The categories of this paper are: econ
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
10
The categories of this paper are: q-bio
29
The categories of this paper are: funct-an
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The categories of this paper are: comp-gas
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph
36
The categories of this paper are: cmp-lg
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The categories of this paper are: eess