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Analysis of institutional authors

Rodriguez ACorresponding AuthorOtero AAuthorDe La Torre, EduardoAuthor

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September 21, 2021
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Exploiting Hardware-Based Data-Parallel and Multithreading Models for Smart Edge Computing in Reconfigurable FPGAs

Publicated to: IEEE TRANSACTIONS ON COMPUTERS. 71 (11): 2903-2914 - 2022-11-01 71(11), DOI: 10.1109/TC.2021.3107196

Authors:

Rodriguez, A; Otero, A; Platzner, M; de la Torre, E
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Affiliations

Centro de Electronica Industrial (CEI), Universidad Politecnica de Madrid - Author
Electrónica Industrial. Universidad Politécnica de Madrid - Author
Univ Paderborn, Dept Comp Sci, D-33098 Paderborn, Germany - Author
Univ Politecn Madrid, Ctr Elect Ind, Madrid 28006, Spain - Author
Universitat Paderborn - Author
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Abstract

Current edge computing systems are deployed in highly complex application scenarios with dynamically changing requirements. In order to provide the expected performance and energy efficiency values in these situations, the use of heterogeneous hardware/software platforms at the edge has become widespread. However, these computing platforms still suffer from the lack of unified software-driven programming models to efficiently deploy multi-purpose hardware-accelerated solutions. In parallel, edge computing systems also face another huge challenge: operating under multiple conditions that were not taken into account during any of the design stages. Moreover, these conditions may change over time, forcing self-adaptation mechanisms to become a must. This paper presents an integrated architecture to exploit hardware-accelerated data-parallel models and transparent hardware/software multithreading. In particular, the proposed architecture leverages the \ARTICo framework and ReconOS to allow developers to select the most suitable programming model to deploy their edge computing applications onto run-time reconfigurable hardware devices. An evolvable hardware system is used as an additional architectural component during validation, providing support for continuous lifelong learning in smart edge computing scenarios. In particular, the proposed setup exhibits online learning capabilities that include learning by imitation from software-based reference algorithms.
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Keywords

architecturecomputational modelingcomputer architecturedata-level parallelismedge computingedge intelligenceevolvable hardwaremultithreadingneural-networksparallel processingreconfigurable computingsoftwaretoolsComputational modelingComputer architectureData-level parallelismEdge computingEdge intelligenceEvolvable hardwareField programmable gate arraysMultithreadingParallel processingProgramming-modelsReconfigurable computingSoftware

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal IEEE TRANSACTIONS ON COMPUTERS due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2022, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Computational Theory and Mathematics.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-26:

  • WoS: 2
  • Scopus: 2
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-26:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 12 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/87621/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 154
  • Downloads: 1
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Germany.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Rodriguez Medina, Alfonso) and Last Author (TORRE ARNANZ, EDUARDO DE LA).

the author responsible for correspondence tasks has been Rodriguez Medina, Alfonso.

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