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Benchmarking open source deep learning frameworks

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 5 (2020)

DOI
10.11591/ijece.v10i5.pp5479-5486
ISSN
2722-2578, 2088-8708
Published
2020-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Deep Learning (DL) is one of the hottest fields. To foster the growth of DL, several open source frameworks appeared providing implementations of the most common DL algorithms. These frameworks vary in the algorithms they support and in the quality of their implementations. The purpose of this work is to provide a qualitative and quantitative comparison among three such frameworks: TensorFlow, Theano and CNTK. To ensure that our study is as comprehensive as possible, we consider multiple benchmark datasets from different fields (image processing, NLP, etc.) and measure the performance of the frameworks' implementations of different DL algorithms. For most of our experiments, we find out that CNTK's implementations are superior to the other ones under consideration.

Collaboration network of the authors

17 authors · 47 co-authorship links · 6 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Jordan University of Science and Technology
  • University of Southampton
  • Yarmouk University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Bashar TalafhaJordan University of Science and Technology1
Analle AbuammarUniversity of Southampton1
Asma’a Al-MnayyisYarmouk University1
Sanaa Abu AlasalJordan University of Science and Technology1
Mohammad A. AlsmiratJordan University of Science and Technology1
Qanita Bani BakerJordan University of Science and Technology1
Amjad NuseirJordan University of Science and Technology1
Hasan AlbalasAffiliation unknown1
Aya NuseirJordan University of Science and Technology1
Maulla AlaliJordan University of Science and Technology1
Firas ZoubiAffiliation unknown1
Mohammed MahdiJordan University of Science and Technology1
Ahmad Al OmariJordan University of Science and Technology1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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