Workflows Community Summit 2024: Future Trends and Challenges in Scientific Workflows

Autor: da Silva, Rafael Ferreira, Bard, Deborah, Chard, Kyle, de Witt, Shaun, Foster, Ian T., Gibbs, Tom, Goble, Carole, Godoy, William, Gustafsson, Johan, Haus, Utz-Uwe, Hudson, Stephen, Jha, Shantenu, Los, Laila, Paine, Drew, Suter, Frédéric, Ward, Logan, Wilkinson, Sean, Amaris, Marcos, Babuji, Yadu, Bader, Jonathan, Balin, Riccardo, Balouek, Daniel, Beecroft, Sarah, Belhajjame, Khalid, Bhattarai, Rajat, Brewer, Wes, Brunk, Paul, Caino-Lores, Silvina, Casanova, Henri, Cassol, Daniela, Coleman, Jared, Coleman, Taina, Colonnelli, Iacopo, Da Silva, Anderson Andrei, de Oliveira, Daniel, Elahi, Pascal, Elfaramawy, Nour, Elwasif, Wael, Etz, Brian, Fahringer, Thomas, Ferreira, Wesley, Filgueira, Rosa, Tande, Jacob Fosso, Gadelha, Luiz, Gallo, Andy, Garijo, Daniel, Georgiou, Yiannis, Gritsch, Philipp, Grubel, Patricia, Gueroudji, Amal, Guilloteau, Quentin, Hamalainen, Carlo, Enriquez, Rolando Hong, Huet, Lauren, Kesling, Kevin Hunter, Iborra, Paula, Jahangiri, Shiva, Janssen, Jan, Jordan, Joe, Kanwal, Sehrish, Kunstmann, Liliane, Lehmann, Fabian, Leser, Ulf, Li, Chen, Liu, Peini, Luettgau, Jakob, Lupat, Richard, Fernandez, Jose M., Maheshwari, Ketan, Malik, Tanu, Marquez, Jack, Matsuda, Motohiko, Medic, Doriana, Mohammadi, Somayeh, Mulone, Alberto, Navarro, John-Luke, Ng, Kin Wai, Noelp, Klaus, Kinoshita, Bruno P., Prout, Ryan, Crusoe, Michael R., Ristov, Sashko, Robila, Stefan, Rosendo, Daniel, Rowell, Billy, Rybicki, Jedrzej, Sanchez, Hector, Saurabh, Nishant, Saurav, Sumit Kumar, Scogland, Tom, Senanayake, Dinindu, Shin, Woong, Sirvent, Raul, Skluzacek, Tyler, Sly-Delgado, Barry, Soiland-Reyes, Stian, Souza, Abel, Souza, Renan, Talia, Domenico, Tallent, Nathan, Thamsen, Lauritz, Titov, Mikhail, Tovar, Benjamin, Vahi, Karan, Vardar-Irrgang, Eric, Vartina, Edite, Wang, Yuandou, Wouters, Merridee, Yu, Qi, Bkhetan, Ziad Al, Zulfiqar, Mahnoor

The Workflows Community Summit gathered 111 participants from 18 countries to discuss emerging trends and challenges in scientific workflows, focusing on six key areas: time-sensitive workflows, AI-HPC convergence, multi-facility workflows, heterogen

Externí odkaz: http://arxiv.org/abs/2410.14943

Curio: A Dataflow-Based Framework for Collaborative Urban Visual Analytics

Autor: Moreira, Gustavo, Hosseini, Maryam, Veiga, Carolina, Alexandre, Lucas, Colaninno, Nicola, de Oliveira, Daniel, Ferreira, Nivan, Lage, Marcos, Miranda, Fabio

Over the past decade, several urban visual analytics systems and tools have been proposed to tackle a host of challenges faced by cities, in areas as diverse as transportation, weather, and real estate. Many of these tools have been designed through

Externí odkaz: http://arxiv.org/abs/2408.06139

ProWis: A Visual Approach for Building, Managing, and Analyzing Weather Simulation Ensembles at Runtime

Autor: de Souza, Carolina Veiga Ferreira, Bonnet, Suzanna Maria, de Oliveira, Daniel, Cataldi, Marcio, Miranda, Fabio, Lage, Marcos

Publikováno v: Published in: IEEE Transactions on Visualization and Computer Graphics ( Volume: 30, Issue: 1, January 2024)

Weather forecasting is essential for decision-making and is usually performed using numerical modeling. Numerical weather models, in turn, are complex tools that require specialized training and laborious setup and are challenging even for weather ex

Externí odkaz: http://arxiv.org/abs/2308.05019

Unikernel Linux (UKL)

Autor: Raza, Ali, Unger, Thomas, Boyd, Matthew, Munson, Eric, Sohal, Parul, Drepper, Ulrich, Jones, Richard, de Oliveira, Daniel Bristot, Woodman, Larry, Mancuso, Renato, Appavoo, Jonathan, Krieger, Orran

Publikováno v: Proceedings of the Eighteenth European Conference on Computer Systems (EuroSys 23), May 2023, Pages 590 - 605

This paper presents Unikernel Linux (UKL), a path toward integrating unikernel optimization techniques in Linux, a general purpose operating system. UKL adds a configuration option to Linux allowing for a single, optimized process to link with the ke

Externí odkaz: http://arxiv.org/abs/2206.00789

Distributed In-memory Data Management for Workflow Executions

Autor: Souza, Renan, Silva, Vítor, Lima, Alexandre A. B., de Oliveira, Daniel, Valduriez, Patrick, Mattoso, Marta

Complex scientific experiments from various domains are typically modeled as workflows and executed on large-scale machines using a Parallel Workflow Management System (WMS). Since such executions usually last for hours or days, some WMSs provide use

Externí odkaz: http://arxiv.org/abs/2105.04720