Track 6 - Multidisciplinary, Domain-Specific and Applied Parallel and Distributed Computing
Chairs
- Antonio Plaza, University of Extremadura, Spain.
- Jose E. Moreira, IBM Thomas J. Watson Research Center, USA.
Program Committee
Salvador Abreu, NOVA-LINCS / University of Evora
Cristiana Bentes, State University of Rio de Janeiro
Vicente Blanco, La Laguna University
Cristina Boeres, Universidade Federal Fluminense
Alvaro Coutinho, High Performance Computing Center
Pasqua D'Ambra, IAC-CNR
Davor Davidovic, Rudjer Boskovic Institute
Juan J. Durillo, Leibniz Supercomputing Centre
Maria Fazio, University of Messina
Stefka Fidanova, Institute of Information and Communication Technologies
Basilio B. Fraguela, Universidade da Coruña
Juan F. R. Herrera, The University of Edinburgh
Fabienne Jezequel, Université Pierre et Marie Curie - Paris 6
Dragi Kimovski, University of Klagenfurt
Juan Angel Lorenzo Del Castillo, CY Cergy Paris Universités
Fabrizio Marozzo, University of Calabria
Xavier Martorell, Universitat Politècnica de Catalunya
Rafael Mayo, CIEMAT
Kary Ocaña, National Laboratory of Scientific Computing
Maria Pantoja, California Polytechnic State University San Luis Obispo
Yiannis Papadopoulos, AMD
Andrea Pietracaprina, University of Padova
Amir Raoofy, Technical University of Munich
Pedro Ribeiro, University of Porto
Natalia Seoane, Universidade de Santiago de Compostela
Pedro Valero-Lara, Oak Ridge National Laboratory
Flavio Vella, University of Trento
Focus
- Applications of numerical algorithms in science and engineering
- Domain-specific libraries and languages in parallel and distributed computing
- Application case-studies for benchmarking and comparative studies of parallel programming models
- Numerical methods for large-scale data analysis
- High-dimensional problems and reduction methods
- Implementation & analysis of parallel numerical algorithms
- Optimization and non-linear problems in parallel and distributed computing
- Parallel numerical linear algebra for dense and sparse matrices
- Partial/ordinary and differential algebraic equations in parallel and distributed computing
- Discrete and combinatorial parallel algorithms
- Parallel metaheuristics and hyperheuristics
- Innovative paradigms, programming models, languages, and libraries for parallel and distributed applications
- Parallel and distributed programming productivity, usability, and component-based parallel programming
- Tensor operations, low-rank approximations
- Data-centric parallel and distributed algorithms for exascale computing
In cooperation
Organized by
Supported by
