Manuel F. Dolz received his BSc degree in computer science from the Universitat Jaume I de Castelló (UJI), Spain, in 2008, and the MSc degree in parallel and distributed computing from the Polytechnic University of Valencia, Spain, in 2010. He obtained his PhD degree from the Universitat Jaume I in 2014. Between 2013 and 2015 he worked as postdoctoral research assistant at the Scientific Computing group from the University of Hamburg, Germany, responsible for the Exa2Green EU-project. In mid-2015, Manuel joined the Universidad Carlos III de Madrid (UC3M) (Spain), where he was responsible for different research activities within the Rephrase EU-Project. Between 2017 and 2018, he was granted with a Juan de la Cierva-Formación (MINECO) and Generalitat Valenciana postdoctoral fellow positions at UC3M and UJI, respectively. Late 2018, Manuel was selected as a talented researcher by the Generalitat Valenciana on a postdoctoral junior position at UJI. Manuel collaborates with national universities (UC3M, UPV) and international institutions (Deutsches Klimarechenzentrum-University of Hamburg, Germany, and École Normale Supériere, Lyon, France). His main research interests are programming models, energy efficiency and deep learning for the high-performance computing domain.

 

Publicaciones más relevantes:

• D. R. del Astorga, M. F. Dolz, J. Fernandez, and J. D. Garcia, “A generic parallel pattern interface for stream and data processing,” Concurrency and Computation: Practice and Experience, p. e4175–n/a, 2017.
• D. R. del Astorga, M. F. Dolz, L. M. Sanchez, J. Fernandez, and J. D. Garcia, “An adaptive offline implementation selector for heterogeneous parallel platforms,” The International Journal of High Performance Computing Applications, 2017.
• D. R. del Astorga, M. F. Dolz, L. M. Sanchez, J. D. Garcia, M. Danelutto, and M. Torquati, “Finding parallel patterns through static analysis in C++ applications,” The International Journal of High Performance Computing Applications, 2017.
• M. F. Dolz, D. R. Astorga, J. Fernandez, M. Torquati, J. D. Garcia, F. Garcia-Carballeira, and M. Danelutto, “Enabling semantics to improve detection of data races and misuses of lock-free data structures,” Concurrency and Computation: Practice and Experience, p. e4114–n/a, 2017.
• P. Llopis, M. F. Dolz, J. Garcia-Blas, F. Isaila, M. R. Heidari, and M. Kuhn, “Analyzing the energy consumption of the storage data path,” The journal of supercomputing, pp. 1-18, 2016.

Proyectos de investigación más relevantes:

• Proyecto Europeo: RePhrase: Refactoring Parallel Heterogeneous Resource-Aware Applications José Daniel García, Comisión Europea, ICT-09-2014, 2015. http://rephrase-eu.weebly.com/
• Proyecto Nacional: Towards Unification Of HPC And Big Data Paradigms Prof. Jesus Carretero and Prof. Félix Garcia Carballeira, Ministerio de Economía y Competitividad, TIN2016-79637-P, 2017. https://www.arcos.inf.uc3m.es/bighpc/

Líneas de investigación: 

• Desarrollo de modelos computacionales y de programación paralelos, aceleración de programas utilizando arquitecturas de última generación (multi-core, GPUs, co-procesadores Xeon Phi...). Evaluación y análisis de aplicaciones mediante herramientas de perfilado y trazado.
• Análisis y aprovechamiento de técnicas de ahorro de energía en las arquitecturas paralelas para la mejora del el rendimiento energético de aplicaciones en plataformas de gran escala. Análisis del consumo mediante medidores de energía.
• Refactorización y transformación de aplicaciones secuenciales de ingeniería a códigos paralelos, con el objetivo de incrementar su rendimiento en plataformas de altas prestaciones.