Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Comparison of Support Vector Machines Training GPU-Accelerated Open
  Source Implementations   Last several years, GPUs are used to accelerate computations in many computer
science domains. We focused on GPU accelerated Support Vector Machines (SVM)
training with non-linear kernel functions. We had searched for all available
GPU accelerated C++ open-source implementations and created an open-source C++
benchmark project. We modifed all the implementations to run on actual hardware
and software and in both Windows and Linux operating systems. The benchmark
project offers making a fair and direct comparison of the individual
implementations under the same conditions, datasets, and hardware. In addition,
we selected the most popular datasets in the community and tested them.
Finally, based on the evaluation, we recommended the best-performing
implementations for dense and sparse datasets.

24
The categories of this paper are: dg-ga
0
The categories of this paper are: hep-ph
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
25
The categories of this paper are: patt-sol
16
The categories of this paper are: stat
8
The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
23
The categories of this paper are: solv-int
37
The categories of this paper are: supr-con
17
The categories of this paper are: q-fin