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César Piñeiro

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2020 – today

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2026
[j12]
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Francisco Javier Cardama, Jorge Vázquez-Pérez, César Piñeiro, Tomás F. Pena, Juan Carlos Pichel, Andrés Gómez:
NetQIR: An extension of QIR for distributed quantum computing. Future Gener. Comput. Syst. 174: 107989 (2026)
[j11]
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César Piñeiro, Juan Carlos Pichel:
OMP4Py: A pure Python implementation of openMP. Future Gener. Comput. Syst. 175: 108035 (2026)
[j10]
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César Piñeiro, Álvaro Vázquez, Juan Carlos Pichel:
Corrigendum to "Towards universal MPI bindings for enhanced new language support" [J. Comput. Sci. 87 (2025), 102557]. J. Comput. Sci. 95: 102674 (2026)
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César Piñeiro, Juan Carlos Pichel:
Unlocking Python Multithreading Capabilities using OpenMP-Based Programming with OMP4Py. CGO 2026: 334-347
2025
[j9]
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David Barral, Francisco Javier Cardama, Guillermo Díaz-Camacho, Daniel Faílde, Iago F. Llovo, Mariamo Mussa-Juane, Jorge Vázquez-Pérez, Juan Villasuso, César Piñeiro, Natalia Costas, Juan Carlos Pichel, Tomás F. Pena, Andrés Gómez:
Review of Distributed Quantum Computing: From single QPU to High Performance Quantum Computing. Comput. Sci. Rev. 57: 100747 (2025)
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César Piñeiro, Álvaro Vázquez, Juan Carlos Pichel:
Towards universal MPI bindings for enhanced new language support. J. Comput. Sci. 87: 102557 (2025)
[j7]
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Francisco Javier Cardama, Jorge Vázquez-Pérez, César Piñeiro, Juan Carlos Pichel, Tomás F. Pena, Andrés Gómez:
Review of intermediate representations for quantum computing. J. Supercomput. 81(2): 418 (2025)
[j6]
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Jorge Vázquez-Pérez, Francisco Javier Cardama, César Piñeiro, Juan Carlos Pichel, Tomás F. Pena, Andrés Gómez:
Inqasm: InQuIR compiler to NetQASM. J. Supercomput. 81(2): 442 (2025)
2024
[j5]
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Jorge Vázquez-Pérez, César Piñeiro, Juan Carlos Pichel, Tomás F. Pena, Andrés Gómez:
QPU integration in OpenCL for heterogeneous programming. J. Supercomput. 80(8): 11682-11703 (2024)
[c3]
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César Piñeiro, Álvaro Vázquez, Juan Carlos Pichel:
MPI4All: Universal Binding Generation for MPI Parallel Programming. ICCS (1) 2024: 196-208
[i3]
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  - journals/corr/abs-2404-01265
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David Barral, Francisco Javier Cardama, Guillermo Díaz, Daniel Faílde, Iago F. Llovo, Mariamo Mussa-Juane, Jorge Vázquez-Pérez, Juan Villasuso, César Piñeiro, Natalia Costas, Juan Carlos Pichel, Tomás F. Pena, Andrés Gómez:
Review of Distributed Quantum Computing. From single QPU to High Performance Quantum Computing. CoRR abs/2404.01265 (2024)
[i2]
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  - journals/corr/abs-2411-14887
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César Piñeiro, Juan Carlos Pichel:
OMP4Py: a pure Python implementation of OpenMP. CoRR abs/2411.14887 (2024)
2022
[j4]
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César Piñeiro, Juan Carlos Pichel:
A unified framework to improve the interoperability between HPC and Big Data languages and programming models. Future Gener. Comput. Syst. 134: 123-139 (2022)
2021
[i1]
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César Piñeiro, Juan Carlos Pichel:
A unified framework to improve the interoperability between HPC and Big Data languages and programming models. CoRR abs/2112.00467 (2021)
2020
[j3]
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  - journals/bioinformatics/PineiroAP20
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César Piñeiro, José Manuel Abuín, Juan Carlos Pichel:
Very Fast Tree: speeding up the estimation of phylogenies for large alignments through parallelization and vectorization strategies. Bioinform. 36(17): 4658-4659 (2020)
[j2]
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César Piñeiro, Rodrigo Martínez-Castaño, Juan Carlos Pichel:
Ignis: An efficient and scalable multi-language Big Data framework. Future Gener. Comput. Syst. 105: 705-716 (2020)
[j1]
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Carlos Eiras-Franco, David Martínez-Rego, Leslie Kanthan, César Piñeiro, Antonio Bahamonde, Bertha Guijarro-Berdiñas, Amparo Alonso-Betanzos:
Fast Distributed kNN Graph Construction Using Auto-tuned Locality-sensitive Hashing. ACM Trans. Intell. Syst. Technol. 11(6): 71:1-71:18 (2020)

2010 – 2019

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2018
[c2]
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  - conf/snams/OteroGPMP18
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Pablo Gamallo Otero, Marcos García, César Piñeiro, Rodrigo Martínez-Castaño, Juan Carlos Pichel:
LinguaKit: A Big Data-Based Multilingual Tool for Linguistic Analysis and Information Extraction. SNAMS 2018: 239-244
2017
[c1]
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César Piñeiro, José Manuel Abuín, Juan Carlos Pichel:
Perldoop2: A Big Data-Oriented Source-to-Source Perl-Java Compiler. DASC/PiCom/DataCom/CyberSciTech 2017: 933-940

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