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Javier Conejero
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2020 – today
- 2024
- [c15]Cristian Catalin Tatu
, Javier Conejero
GPU Cache System for COMPSs: A Task-Based Distributed Computing Framework. Euro-Par (3) 2024: 225-239 - 2023
- [j8]Arnau Folch
The EU Center of Excellence for Exascale in Solid Earth (ChEESE): Implementation, results, and roadmap for the second phase. Future Gener. Comput. Syst. 146: 47-61 (2023) - [c14]Francesc Lordan
Hierarchical Management of Extreme-Scale Task-Based Applications. Euro-Par 2023: 111-124 - [c13]Fernando Vázquez-Novoa
Scalable Random Forest with Data-Parallel Computing. Euro-Par 2023: 397-410 - 2022
- [j7]Rosa M. Badia
PyCOMPSs as an Instrument for Translational Computer Science. Comput. Sci. Eng. 24(2): 79-84 (2022) - [c12]Jorge Ejarque, Pau Andrio
The BioExcel methodology for developing dynamic, scalable, reliable and portable computational biomolecular workflows. e-Science 2022: 357-366 - [c11]Raül Sirvent, Javier Conejero, Francesc Lordan
Automatic, Efficient and Scalable Provenance Registration for FAIR HPC Workflows. WORKS@SC 2022: 1-9 - [i3]Sergio Sánchez Ramírez, Javier Conejero, Francesc Lordan, Anna Queralt, Toni Cortes, Rosa M. Badia, Artur García-Sáez:
RosneT: A Block Tensor Algebra Library for Out-of-Core Quantum Computing Simulation. CoRR abs/2201.06620 (2022) - [i2]Jorge Ejarque, Pau Andrio
The BioExcel methodology for developing dynamic, scalable, reliable and portable computational biomolecular workflows. CoRR abs/2208.14130 (2022) - 2020
- [c10]Jorge Ejarque
Managing Failures in Task-Based Parallel Workflows in Distributed Computing Environments. Euro-Par 2020: 411-425 - [c9]Clément Foyer
Enabling System Wide Shared Memory for Performance Improvement in PyCOMPSs Applications. PyHPC@SC 2020: 22-31 - [i1]Rosa M. Badia, Jorge Ejarque, Francesc Lordan, Daniele Lezzi, Javier Conejero, Javier Álvarez Cid-Fuentes, Yolanda Becerra, Anna Queralt:
Workflow environments for advanced cyberinfrastructure platforms. CoRR abs/2006.07066 (2020)
2010 – 2019
- 2019
- [c8]Rosa M. Badia, Jorge Ejarque
Workflow Environments for Advanced Cyberinfrastructure Platforms. ICDCS 2019: 1720-1729 - [c7]Albert Njoroge Kahira
Accelerating Hyperparameter Optimisation with PyCOMPSs. ICPP Workshops 2019: 20:1-20:8 - 2018
- [j6]Javier Conejero
Task-based programming in COMPSs to converge from HPC to big data. Int. J. High Perform. Comput. Appl. 32(1): 45-60 (2018) - [c6]Javier Conejero
Boosting Atmospheric Dust Forecast with PyCOMPSs. eScience 2018: 464-474 - 2017
- [c5]Ramon Amela, Cristian Ramon-Cortes
Enabling Python to execute efficiently in heterogeneous distributed infrastructures with PyCOMPSs. PyHPC@SC 2017: 1:1-1:10 - 2016
- [j5]Javier Conejero
Analyzing Hadoop power consumption and impact on application QoS. Future Gener. Comput. Syst. 55: 213-223 (2016) - [j4]M. Carmen Ruiz
Formal performance evaluation of the Map/Reduce framework within cloud computing. J. Supercomput. 72(8): 3136-3155 (2016) - 2015
- [j3]Pete Burnap
COSMOS: Towards an integrated and scalable service for analysing social media on demand. Int. J. Parallel Emergent Distributed Syst. 30(2): 80-100 (2015) - 2014
- [j2]Javier Conejero
From volunteer to trustable computing: Providing QoS-aware scheduling mechanisms for multi-grid computing environments. Future Gener. Comput. Syst. 34: 76-93 (2014) - [c4]Javier Conejero
Analysing Hadoop performance in a multi-user IaaS Cloud. HPCS 2014: 399-406 - 2013
- [c3]Javier Conejero
Scaling Archived Social Media Data Analysis Using a Hadoop Cloud. IEEE CLOUD 2013: 685-692 - [c2]Javier Conejero, Omer F. Rana, Pete Burnap, Jeffrey Morgan, Carmen Carrión, María Blanca Caminero:
Characterising the Power Consumption of Hadoop Clouds - A Social Media Analysis Case Study. CLOSER 2013: 233-243 - 2012
- [j1]Javier Conejero, Luis Tomás, María Blanca Caminero, Carmen Carrión:
QoS Provisioning by Meta-Scheduling in Advance within SLA-Based Grid Environments. Comput. Informatics 31(1): 73-88 (2012) - [c1]Javier Conejero
Multilevel SLA-based QoS Support in Grids. ISPA 2012: 239-246
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