Publications

[1] I. Martín-Álvarez, J. Aliaga, M. Castillo, and S. Iserte, "Proteo: a framework for the generation and evaluation of malleable MPI applications." The Journal of Supercomputing, Jul. 2024. ISSN: 1573-0484. https://doi.org/10.1007/s11227-024-06277-5

[2] A. Tarraf, M. Schreiber, A. Cascajo, J. Besnard, M. Vef, D. Huber, S. Happ, A. Brinkmann, D. Singh, H. Hoppe, A. Miranda, A. Peña, R. Machado, M. Gasulla, M. Schulz, P. Carpenter, S. Pickartz, T. Rotaru, S. Iserte, V. Lopez, J. Ejarque, H. Sirwani, and F. Wolf, "Malleability in Modern HPC Systems: Current Experiences, Challenges, and Future Opportunities." IEEE Transactions on Parallel and Distributed Systems, pp. 1--14, Jun. 2024. ISSN: 1558-2183. https://doi.org/10.1109/TPDS.2024.3406764

[3] R. Martínez-Cuenca, J. Luis-Gómez, S. Iserte, and S. Chiva, "On the Use of Deep Learning and Computational Fluid Dynamics for the Estimation of Uniform Momentum Source Components of Propellers." iScience(26), pp. 1--14, Oct. 2023. https://doi.org/10.1016/j.isci.2023.108297

[4] P. Rosciszewski, A. Krzywaniak, S. Iserte, K. Rojek, and P. Gepner, "Optimizing Throughput of Seq2Seq Model Training on the IPU Platform for AI-accelerated CFD Simulations." Future Generation Computer Systems(143), pp. 149--162, May 2023. https://doi.org/10.1016/j.future.2023.05.004

[5] I. Martín-Álvarez, J. Aliaga, M. Castillo, S. Iserte, and R. Mayo, "Dynamic spawning of MPI processes applied to malleability." International Journal of High Performance Computing Applications(0), pp. 1--25, May 2023. https://doi.org/10.1177/10943420231176527

[6] S. Iserte, A. González-Barberá, P. Barreda, and K. Rojek, "A Study on the Performance of Distributed Training of Data-driven CFD Simulations." International Journal of High Performance Computing Applications(37), pp. 503--515, May 2023. ISSN: 1094-3420. https://doi.org/10.1177/10943420231160557

[7] S. Iserte, V. Tomas, M. Pérez, M. Castillo, P. Boronat, and L. Amable, "Complete Integration of Team Project-based Learning into a Database Syllabus." IEEE Transactions on Education(3), pp. 1--8, Nov. 2022. ISSN: 0018-9359. https://doi.org/10.1109/TE.2022.3217309

[8] S. Iserte, A. Macías, R. Martínez-Cuenca, S. Chiva, R. Paredes, and E. Quintana-Ortí, "Accelerating Urban Scale Simulations Leveraging Local Spatial 3D Structure." Journal of Computational Science(62), pp. 1--11, Jul. 2022. ISSN: 1877-7503. https://doi.org/10.1016/j.jocs.2022.101741

[9] J. Aliaga, M. Castillo, S. Iserte, I. Martín-Álvarez, and R. Mayo, "A Survey on Malleability Solutions for High-Performance Distributed Computing." Applied Science(12), pp. 1--32, May 2022. ISSN: 2076-3417. https://doi.org/10.3390/app12105231

[10] S. Iserte, P. Carratalà, R. Arnau, R. Martínez-Cuenca, P. Barreda, L. Basiero, J. Climent, and S. Chiva, "Modeling of Wastewater Treatment Processes with HydroSludge." Water Environment Research(93), pp. 3049--3063, Oct. 2021. ISSN: 1061-4303. https://doi.org/10.1002/wer.1656

[11] S. Catalán, R. Carratalá-Sáez, and S. Iserte, "Leveraging Teaching on Demand: Approaching HPC to Undergrads." Journal of Parallel and Distributed Computing(156), pp. 148--162, Oct. 2021. ISSN: 0743-7315. https://doi.org/10.1016/j.jpdc.2021.05.015

[12] S. Iserte, and K. Rojek, "A Study of the Effect of Process Malleability in the Energy Efficiency on GPU-based Clusters." Journal of Supercomputing(76), pp. 255--274, Oct. 2020. ISSN: 0920-8542. https://doi.org/10.1007/s11227-019-03034-x

[13] S. Iserte, R. Mayo, E. Quintana-Ortí, and A. Peña, "DMRlib: Easy-coding and Efficient Resource Management for Job Malleability." IEEE Transactions on Computers(70), pp. 1443--1457, Sep. 2020. ISSN: 0018-9340. https://doi.org/10.1109/TC.2020.3022933

[14] F. Silla, S. Iserte, C. Reaño, and J. Prades, "Improving the Management Efficiency of GPU Workloads in Data Centers through GPU Virtualization." Concurrency and Computation: Practice and Experience(33), pp. 1--10, Apr. 2019. ISSN: 1532-0626. https://doi.org/10.1002/cpe.5275

[15] S. Iserte, H. Martínez, S. Barrachina, M. Castillo, R. Mayo, and A. Peña, "Dynamic Reconfiguration of Non-iterative Scientific Applications: A Case Study with HPG-aligner." International Journal of High Performance Computing Application(33), pp. 1--10, Aug. 2018. ISSN: 1094-3420. https://doi.org/10.1177/1094342018802347

[16] S. Iserte, R. Peña-Ortíz, J. Gutiérrez-Aguado, J. Claver, and R. Mayo, "GSaaS: A Service to Cloudify and Schedule GPUs." IEEE Access(6), pp. 39762--39774, Jul. 2018. ISSN: 2169-3536. https://doi.org/10.1109/ACCESS.2018.2855261

[17] S. Iserte, R. Mayo, E. Quintana-Ortí, V. Beltran, and A. Peña, "DMR API: Improving Cluster Productivity by Turning Applications into Malleable." Parallel Computing(78), pp. 54--66, Jul. 2018. ISSN: 0167-8191. https://doi.org/10.1016/j.parco.2018.07.006

[18] F. Silla, S. Iserte, C. Reaño, and J. Prades, "On the Benefits of the Remote GPU Virtualization Mechanism: the rCUDA Case." Concurrency and Computation: Practice and Experience(29), pp. 1--10, Feb. 2017. ISSN: 1532-0634. https://doi.org/10.1002/cpe.4072

[19] M. Dolz, J. Fernández, S. Iserte, R. Mayo, and E. Quintana, "A Simulator to Assess Energy Saving Strategies and Policies in HPC Workloads." ACM Operating Systems Review(49), pp. 2--9, Jul. 2012. ISSN: 0163-5980. https://doi.org/10.1145/2331576.2331578

[1] S. Iserte, I. Martín-Álvarez, K. Rojek, J. Aliaga, M. Castillo, and A. Peña, "Towards the Democratization and Standardization of Dynamic Resources with MPI Spawning." PPAM Proceedings - Best Paper Award, Sep. 2024.

[2] K. Halbiniak, K. Rojek, S. Iserte, and R. Wyrzykowski, "Unleashing the Potential of Mixed Precision in AI-Accelerated CFD Simulation on Intel CPU/GPU Architectures." Computational Science – ICCS 2024, pp. 203--217, Mar. 2024. https://doi.org/10.1007/978-3-031-63778-0_15

[3] I. Martín-Álvarez, J. Aliaga, M. Castillo, and S. Iserte, "Configurable Synthetic Application for Studying Malleability in HPC." 31st Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP), Mar. 2023. https://doi.org/10.1109/PDP59025.2023.00027

[4] F. Majó, P. Barreda, and S. Iserte, "A Distributed Mesh Generation Study Case through a Customizable Platform as a Service Framework." 11th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH), Jul. 2021. https://doi.org/10.5220/0010576904140421

[5] V. Tomás, S. Iserte, and M. Pérez, "Learning Databases Using Project-based Learning." 15th International Technology, Education and Development Conference (INTED), Mar. 2021.

[6] A. Castelló, S. Iserte, and A. Belloch, "Accessible C-programming course from scratch using a MOOC platform without limitations." 4th International Conference on Higher Education Advances (HEAD), Jun. 2018. https://doi.org/10.4995/HEAd18.2018.8176

[7] S. Iserte, J. Prades, C. Reaño, and F. Silla, "Increasing the Performance of Data Centers by Combining Remote GPU Virtualization with Slurm." 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), May 2016. https://doi.org/10.1109/CCGrid.2016.26

[8] S. Iserte, F. Clemente-Castelló, A. Castelló, R. Mayo, and E. Quintana-Ortí, "Enabling GPU Virtualization in Cloud Environments." 6th International Conference on Cloud Computing and Services Science (CLOSER), Apr. 2016. https://doi.org/10.5220/0005780502490256

[9] S. Iserte, A. Castelló, R. Mayo, E. Quintana-Ortí, C. Reaño, J. Prades, F. Silla, and J. Duato, "Slurm Support for Remote GPU Virtualization: Implementation and Performance Study." 26th Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Oct. 2014. https://doi.org/10.1109/SBAC-PAD.2014.49

[10] M. Dolz, J. Fernández, S. Iserte, R. Mayo, E. Quintana, M. Cotallo, and G. Díaz, "EnergySaving Cluster Experience in CETA-CIEMAT." 5th Iberian Grid Infrastructure Conference (IBERGRID), Jun. 2011.

[1] S. Iserte, V. Lopez, M. Garcia-Gasulla, and A. Peña, "Parallel Efficiency-aware Standard MPI-based Malleability." Euro-par Workshops Proceedings, Aug. 2024.

[2] I. Martín, M. Castillo, J. Aliaga, and S. Iserte, "Efficient Data Redistribution for Malleable Applications." ExaMPI23 held in conjunction with SC, Nov. 2023. https://doi.org/10.1145/3624062.3624110

[3] M. Usman, S. Iserte, R. Ferrer, and A. Peña, "DPU Offloading Programming with the OpenMP API." LLVM-HPC23 held in conjunction with SC, Nov. 2023. https://doi.org/10.1145/3624062.3624165

[4] P. Rosciszewski, A. Krzywaniak, S. Iserte, K. Rojek, and P. Gepner, "Adaptation of AI-accelerated CFD Simulations to the IPU platform." 1st Workshop on Applications of Machine Learning and Artificial Intelligence in High-Performance Computing (WAML-HPC) held in conjunction with PPAM, Sep. 2022. https://doi.org/10.1007/978-3-031-30445-3_19

[5] R. Carratalá, S. Iserte, and S. Catalán, "Teaching on Demand: an HPC Experience." Workshop on Education for High Performance Computing (EduHPC) held in conjunction with SC, Nov. 2019. https://doi.org/10.1109/EduHPC49559.2019.00010

[6] S. Iserte, A. Peña, and R. Mayo, "Boosting Productivity through Efficient Resource Management." ACM/IFIP International Middleware Conference, Doctoral Symposium, Dec. 2018.

[7] S. Iserte, A. Peña, and R. Mayo, "Productivity-enhancing malleability for HPC applications." 27th International Conference on Parallel Architectures and Compilation Techniques (PACT18), ACM Student Research Competition (SRC), Nov. 2018.

[8] S. Iserte, R. Mayo, E. Quintana-Ortí, V. Beltran, and A. Peña, "Efficient Scalable Computing through Flexible Applications and Adaptive Workloads." 10th International Workshop on Parallel Programming Models and Systems Software for High-End Computing (P2S2) held in conjunction with IPDPS, Aug. 2017. https://doi.org/10.1109/ICPPW.2017.36

[9] F. Silla, J. Prades, S. Iserte, and C. Reaño, "Remote GPU Virtualization: Is It Useful?." 2nd IEEE International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era (HiPINEB), Mar. 2016. https://doi.org/10.1109/HIPINEB.2016.8

[10] S. Iserte, A. Peña, R. Mayo, E. Quintana-Ortí, and V. Beltran, "Dynamic Management of Resource Allocation for OmpSs Jobs." 1st PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD), Feb. 2016.

[11] M. Dolz, J. Fernández, S. Iserte, R. Mayo, and E. Quintana, "A Flexible Simulator to Evaluate a Power Saving System for HPC Clusters." 2nd International Workshop on Green Computing Middleware (GCM), Dec. 2011.

[1] S. Iserte, "A Study on the Resource Utilization and User Behavior on Titan Supercomputer." Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation(1512), pp. 1-8, Mar. 2022. https://doi.org/10.1007/978-3-030-96498-6_23

[2] S. Iserte, S. Catalán, R. Carratalá-Saez, and S. López, "Construya su propio supercomputador con Raspberri Pi." Construya su propio supercomputador con Raspberri Pi, May 2021. https://www.marcombo.com/libro/libros-tecnicos-y-cientificos/electronica-libros-tecnicos-y-cientificos/raspberry-pi-electronica/construya-su-propio-supercomputador-con-raspberry-pi/

[1] S. Iserte, V. Lopez, M. Garcia-Gasulla, and A. Peña, "Maleabilidad MPI basada en la eficiencia paralela." XXXIII Jornadas SARTECO, Sep. 2023.

[2] A. González-Barberá, P. Barreda, K. Rojek, and S. Iserte, "Estudio del rendimiento en entrenamientos distribuidos para simulaciones CFD data-driven." XXXIII Jornadas SARTECO, Sep. 2023.

[3] I. Martín-Álvarez, J. Aliaga, M. Castillo, and S. Iserte, "Análisis de métodos de redistribución de datos para aplicaciones MPI maleables." XXXIII Jornadas SARTECO, Sep. 2023.

[4] I. Martín-Álvarez, J. Aliaga, M. Castillo, S. Iserte, and R. Mayo, "Aplicación sintética para el estudio de maleabilidad en computación de altas prestaciones." XXXII Jornadas SARTECO, Sep. 2022. http://hdl.handle.net/10234/200777

[5] V. Tomás, M. Castillo, M. Pérez, P. Boronat, L. Amable, and S. Iserte, "Improving Basic Competences Through Project-based Learning and Teamworking." VI Congreso Internacional sobre Aprendizaje, Innovación y Cooperación (CINAIC), Oct. 2021. https://doi.org/10.26754/uz.978-84-18321-17-7

[6] J. Agustina, R. Cuenca, J. Vilarroig, R. Arnau, L. Basiero, R. Tirado, S. Iserte, and S. Chiva, "Desarrollo de una herramienta de simulación computacional 3D aplicada a procesos de depuración de aguas residuales." VI Jornadas de Ingeniería del Agua, Oct. 2019. https://www.hidralab.com:4430/jia2019/wp-content/uploads/2019/10/R170.pdf

[7] S. Iserte, R. Mayo, E. Quintana-Ortí, V. Beltran, and A. Peña, "El camino desde la maleabilidad MPI hasta las cargas de trabajos adapativas." XXVIII Jornadas SARTECO, Sep. 2017.

[8] S. Iserte, A. Castelló, R. Mayo, E. Quintana-Ortí, J. Prades, C. Reaño, F. Silla, and J. Duato, "Comparativa de políticas de selección de GPUs remotas en clusters HPC." XXVI Jornadas SARTECO, Sep. 2015.

[9] S. Iserte, A. Castelló, R. Mayo, E. Quintana-Ortí, J. Prades, C. Reaño, F. Silla, and J. Duato, "Extendiendo SLURM con soporte para el uso de GPUs remotas." XXV Jornadas SARTECO, Sep. 2014.

[10] C. Reaño, A. Castelló, S. Iserte, A. Peña, F. Silla, R. Mayo, E. Quintana-Ortí, and J. Duato, "Virtualización remota de GPUs: Evaluación de soluciones disponibles para CUDA." XXIV Jornadas SARTECO, Sep. 2013.

[11] S. Iserte, A. Castelló, C. Reaño, A. Peña, F. Silla, R. Mayo, E. Quintana-Ortí, and J. Duato, "Un planificador de GPUs remotas para clusters HPC." XXIV Jornadas SARTECO, Sep. 2013.

[1] P. Dutot, J. Fecht, K. Gaddameedi, D. Huber, S. Iserte, M. Minion, M. Schulz, M. Schreiber, V. Schüller, A. Peña, and O. Richard, "Leveraging Dynamic Resource Management in HPC." ISC, Jun. 2024.

[2] S. Iserte, M. Morales-Hernández, J. Segovia, P. Vallés, D. Caviedes-Voullième, and A. Peña, "Dynamic Resources Utilization in Malleable Flooding Simulations." 16th JLESC, Apr. 2024.

[3] M. Usman, S. Iserte, R. Ferrer, and A. Peña, "BlueField DPU Programming using OpenMP Offloading." IEEE CLUSTER, Nov. 2023.

[4] I. Martín, J. Aliaga, M. Castillo, R. Mayo, and S. Iserte, "Malleability Implementation in a MPI Iterative Method." IEEE CLUSTER, Sep. 2021. ISSN: 978-1-7281-9666-4. https://doi.org/10.1109/Cluster48925.2021.00078

[5] S. Iserte, H. Martínez, S. Barrachina, M. Castillo, R. Mayo, E. Quintana-Ortí, and A. Peña, "MPI Malleability Integration into a Bioinformatics Tool." Euro/USA MPI Conference, Sep. 2018.

[6] S. Iserte, R. Mayo, E. Quintana-Ortí, and A. Peña, "High-throughput Computation through MPI Malleability." Advanced Computer Architecture and Compilation for High-Performance and Embedded Systems (ACACES), Jul. 2018. ISSN: 978-88-905806-6-6.

[7] F. Silla, C. Reaño, J. Prades, and S. Iserte, "Benefits of remote GPU virtualization: the rCUDA perspective." GPU Technology Conference (GTC), Apr. 2016.

[8] S. Iserte, F. Clemente, R. Mayo, and E. Quintana-Ortí, "GPU Virtualization in the Cloud." Advanced Computer Architecture and Compilation for High-Performance and Embedded Systems (ACACES), Jul. 2015. ISSN: 978-88-905806-3-5.