Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Exploring the Impact of Virtualization on the Usability of the Deep
  Learning Applications   Deep Learning-based (DL) applications are becoming increasingly popular and
advancing at an unprecedented pace. While many research works are being
undertaken to enhance Deep Neural Networks (DNN) -- the centerpiece of DL
applications -- practical deployment challenges of these applications in the
Cloud and Edge systems, and their impact on the usability of the applications
have not been sufficiently investigated. In particular, the impact of deploying
different virtualization platforms, offered by the Cloud and Edge, on the
usability of DL applications (in terms of the End-to-End (E2E) inference time)
has remained an open question. Importantly, resource elasticity (by means of
scale-up), CPU pinning, and processor type (CPU vs GPU) configurations have
shown to be influential on the virtualization overhead. Accordingly, the goal
of this research is to study the impact of these potentially decisive
deployment options on the E2E performance, thus, usability of the DL
applications. To that end, we measure the impact of four popular execution
platforms (namely, bare-metal, virtual machine (VM), container, and container
in VM) on the E2E inference time of four types of DL applications, upon
changing processor configuration (scale-up, CPU pinning) and processor types.
This study reveals a set of interesting and sometimes counter-intuitive
findings that can be used as best practices by Cloud solution architects to
efficiently deploy DL applications in various systems. The notable finding is
that the solution architects must be aware of the DL application
characteristics, particularly, their pre- and post-processing requirements, to
be able to optimally choose and configure an execution platform, determine the
use of GPU, and decide the efficient scale-up range.

14
The categories of this paper are: math-ph
15
The categories of this paper are: nucl-ex
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
16
The categories of this paper are: stat
11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
19
The categories of this paper are: eess
17
The categories of this paper are: q-fin
37
The categories of this paper are: supr-con
6
The categories of this paper are: astro-ph
25
The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th