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Analysis of institutional authors

Quintana-Orti, Enrique SAuthorTomas, Andres ECorresponding Author

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October 16, 2024
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Article

Compression and load balancing for efficient sparse matrix-vector product on multicore processors and graphics processing units

Publicated to: Concurrency and Computation Practice and Experience. 34 (14): 1-13 - 2022-01-01 34(14), DOI: 10.1002/cpe.6515

Authors:

Aliaga, José I.; Anzt, Hartwig; Grützmacher, Thomas; Quintana-Ortí, Enrique S.; Tomás Domínguez, Andrés Enrique
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Affiliations

Karlsruhe Inst Technol, Karlsruhe, Germany - Author
Univ Jaume 1, Dept Ingn & Ciencia Computadores, Castellon De La Plana, Spain - Author
Univ Politecn Valencia, Dept Informat Sistemas & Computadores, Valencia, Spain - Author
Univ Tennessee, Innovat Comp Lab, Knoxville, TN USA - Author
Univ Valencia, Dept Informat, Valencia, Spain - Author
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Abstract

We contribute to the optimization of the sparse matrix-vector product by introducing a variant of the coordinate sparse matrix format that balances the workload distribution and compresses both the indexing arrays and the numerical information. Our approach is multi-platform, in the sense that the realizations for (general-purpose) multicore processors as well as graphics accelerators (GPUs) are built upon common principles, but differ in the implementation details, which are adapted to avoid thread divergence in the GPU case or maximize compression element-wise (i.e., for each matrix entry) for multicore architectures. Our evaluation on the two last generations of NVIDIA GPUs as well as Intel and AMD processors demonstrate the benefits of the new kernels when compared with the optimized implementations of the sparse matrix-vector product in NVIDIA's cuSPARSE and Intel's MKL, respectively.
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Keywords

CompressionCoordinate sparse matrix formatGraphics processing units (gpus)Multicore processors (cpus)Multicore processors (cpus)Sparse matrix-vector productWorkload balancinWorkload balancingWorkload balancing.

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

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 2026-04-05:

  • WoS: 15
  • Scopus: 17
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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 2026-04-05:

  • 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: 7 (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:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: http://hdl.handle.net/10251/196280
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Germany; United States of America.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: Last Author (Tomás Domínguez, Andrés Enrique).

the author responsible for correspondence tasks has been Tomás Domínguez, Andrés Enrique.

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Awards linked to the item

DoE - USA, Grant/Award Number: Exascale computing project 17-SC-20-SC; Helmholtz Association, Grant/Award Number: VH-NG-1241; SpanishMINECO, Grant/Award Number: TIN2017-82972-R
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