The SONATA data format for efficient description of large-scale network models.

Autor: Kael Dai, Juan Hernando, Yazan N Billeh, Sergey L Gratiy, Judit Planas, Andrew P Davison, Salvador Dura-Bernal, Padraig Gleeson, Adrien Devresse, Benjamin K Dichter, Michael Gevaert, James G King, Werner A H Van Geit, Arseny V Povolotsky, Eilif Muller, Jean-Denis Courcol, Anton Arkhipov

Publikováno v: PLoS Computational Biology, Vol 16, Iss 2, p e1007696 (2020)

Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simu

Externí odkaz: https://doaj.org/article/96cd62f444274b59b61eee3ed7ac4d6c

Modeling and Simulation of Rat Non-Barrel Somatosensory Cortex. Part I: Modeling Anatomy

Autor: Michael W. Reimann, Sirio Bolaños-Puchet, Jean-Denis Courcol, Daniela Egas Santander, Alexis Arnaudon, Benoît Coste, Thomas Delemontex, Adrien Devresse, Hugo Dictus, Alexander Dietz, András Ecker, Cyrille Favreau, Gianluca Ficarelli, Mike Gevaert, Juan B. Hernando, Joni Herttuainen, James B. Isbister, Lida Kanari, Daniel Keller, James King, Pramod Kumbhar, Samuel Lapere, Jānis Lazovskis, Huanxiang Lu, Nicolas Ninin, Fernando Pereira, Judit Planas, Christoph Pokorny, Juan Luis Riquelme, Armando Romani, Ying Shi, Jason P. Smith, Vishal Sood, Mohit Srivastava, Werner Van Geit, Liesbeth Vanherpe, Matthias Wolf, Ran Levi, Kathryn Hess, Felix Schürmann, Eilif B. Muller, Srikanth Ramaswamy, Henry Markram

The function of the neocortex is fundamentally determined by its repeating microcircuit motif, but also by its rich, hierarchical, interregional structure with a highly specific laminar architecture. The last decade has seen the emergence of extensiv

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fe627eb2c78c5eb420f9c4c1179d84b0
https://doi.org/10.1101/2022.08.11.503144

Exploring the interoperability of remote GPGPU virtualization using rCUDA and directive-based programming models

Autor: Adrián Castelló, Antonio J. Peña, Judit Planas, Rafael Mayo, Enrique S. Quintana-Ortí, Pavan Balaji

Publikováno v: Repositori Universitat Jaume I
Universitat Jaume I
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Recercat. Dipósit de la Recerca de Catalunya
instname
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia

[EN] Directive-based programming models, such as OpenMP, OpenACC, and OmpSs, enable users to accelerate applications by using coprocessors with little effort. These devices offer significant computing power, but their use can introduce two problems:

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7983c693f62659b321e6d5b5621512b8
https://doi.org/10.1007/s11227-016-1791-y

Accelerating Data Analysis in Simulation Neuroscience with Big Data Technologies

Autor: Judit Planas, Fabien Delalondre, Felix Schürmann

Publikováno v: Lecture Notes in Computer Science ISBN: 9783319936970
ICCS (1)

Important progress in computational sciences has been made possible recently thanks to the increasing computing power of high performance systems. Following this trend, larger scientific studies, like brain tissue simulations, will continue to grow i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bd6bbd354e678d79022fd9263ee7c893
https://doi.org/10.1007/978-3-319-93698-7_28

Key/Value-Enabled Flash Memory for Complex Scientific Workflows with On-Line Analysis and Visualization

Autor: Judit Planas, Blake G. Fitch, Costas Bekas, Stefan Eilemann, T. J. Christopher Ward, Ralph Bellofatto, Bernard Metzler, John Biddiscombe, Alessandro Curioni, Joachim Fenkes, Felix Schuermann, Peter Morjan, Lars Schneidenbach, Peter Kaltstein, Jon Bernard, Fabien Delalondre

Publikováno v: IPDPS

Scientific workflows are often composed of compute-intensive simulations and data-intensive analysis and visualization, both equally important for productivity. High-performance computers run the compute-intensive phases efficiently, but data-intensi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a48347d4001a00fccfaedda4d2f0834
https://doi.org/10.1109/ipdps.2016.23