Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On the Performance of Network Parallel Training in Artificial Neural
  Networks   Artificial Neural Networks (ANNs) have received increasing attention in
recent years with applications that span a wide range of disciplines including
vital domains such as medicine, network security and autonomous transportation.
However, neural network architectures are becoming increasingly complex and
with an increasing need to obtain real-time results from such models, it has
become pivotal to use parallelization as a mechanism for speeding up network
training and deployment. In this work we propose an implementation of Network
Parallel Training through Cannon's Algorithm for matrix multiplication. We show
that increasing the number of processes speeds up training until the point
where process communication costs become prohibitive; this point varies by
network complexity. We also show through empirical efficiency calculations that
the speedup obtained is superlinear.

28
The categories of this paper are: alg-geom
22
The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
36
The categories of this paper are: cmp-lg
37
The categories of this paper are: supr-con
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
29
The categories of this paper are: funct-an
3
The categories of this paper are: physics
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
25
The categories of this paper are: patt-sol