Paola Caymes-Scutari

According to our database, Paola Caymes-Scutari authored at least 23 papers between 2005 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Evolutionary Statistical System Based on Novelty Search: A Parallel Metaheuristic for Uncertainty Reduction Applied to Wildfire Spread Prediction.

Jan Strappa, Paola Caymes-Scutari, Germán Bianchini

Algorithms, 2022

A Parallel Novelty Search Metaheuristic Applied to a Wildfire Prediction System.

Jan Strappa, Paola Caymes-Scutari, Germán Bianchini

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

2021

HESS-IM: A Uncertainty Reduction Method that Integrates Remote Sensing Data Applied to Forest Fire Behavior Prediction.

Miguel Méndez-Garabetti, Germán Bianchini, Paola Caymes-Scutari

Proceedings of the Cloud Computing, Big Data & Emerging Topics - 9th Conference, 2021

2019

Dynamic Tuning of a Forest Fire Prediction Parallel Method.

Paola Caymes-Scutari, María Laura Tardivo, Germán Bianchini, Miguel Méndez-Garabetti

Proceedings of the Computer Science - CACIC 2019, 2019

2017

Hierarchical parallel model for improving performance on differential evolution.

María Laura Tardivo, Paola Caymes-Scutari, Germán Bianchini, Miguel Méndez-Garabetti

Concurr. Comput. Pract. Exp., 2017

A comparative study of evolutionary statistical methods for uncertainty reduction in forest fire propagation prediction.

María Laura Tardivo, Paola Caymes-Scutari, Germán Bianchini, Miguel Méndez-Garabetti, Andrés Cencerrado, Ana Cortés

Proceedings of the International Conference on Computational Science, 2017

Optimization for an Uncertainty Reduction Method Applied to Forest Fires Spread Prediction.

María Laura Tardivo, Paola Caymes-Scutari, Miguel Méndez-Garabetti, Germán Bianchini

Proceedings of the Computer Science - CACIC 2017, 2017

2016

ESS-IM applied to forest fire spread prediction: Parameters tuning for a heterogeneous configuration.

Miguel Méndez-Garabetti, Germán Bianchini, Paola Caymes-Scutari, María Laura Tardivo

Proceedings of the 35th International Conference of the Chilean Computer Science Society, 2016

Three evolutionary statistical parallel methods for uncertainty reduction in wildland fire prediction.

María Laura Tardivo, Paola Caymes-Scutari, Germán Bianchini, Miguel Méndez-Garabetti, Ana Cortés

Proceedings of the International Conference on High Performance Computing & Simulation, 2016

Environment for automatic development and tuning of parallel applications.

Paola Caymes-Scutari, Germán Bianchini, Anna Sikora, Tomàs Margalef

Proceedings of the International Conference on High Performance Computing & Simulation, 2016

2015

Evolutionary-Statistical System: A parallel method for improving forest fire spread prediction.

Germán Bianchini, Paola Caymes-Scutari, Miguel Méndez-Garabetti

J. Comput. Sci., 2015

2014

Comparative Analysis of Performance and Quality of Prediction Between ESS and ESS-IM.

Miguel Méndez-Garabetti, Germán Bianchini, María Laura Tardivo, Paola Caymes-Scutari

Proceedings of the XL Latin American Computer Conference - Selected Papers, 2014

Tuned Forest Fire Prediction: Static Calibration of the Evolutionary Component of ESS.

Germán Bianchini, Paola Caymes-Scutari

CLEI Electron. J., 2014

2013

Estimation of Volume Rendering Efficiency with GPU in a Parallel Distributed Environment.

Cristian Federico Perez Montea, Fabiana Piccoli, Cristian Luciano, Silvio H. R. Rizzi, Germán Bianchini, Paola Caymes-Scutari

Proceedings of the International Conference on Computational Science, 2013

Calibration of the parameters of ESS system for Forest Fire prediction.

Germán Bianchini, Paola Caymes-Scutari

Proceedings of the 2013 XXXIX Latin American Computing Conference (CLEI), 2013

2012

A methodology for transparent knowledge specification in a dynamic tuning environment.

Paola Caymes-Scutari, Anna Morajko, Tomàs Margalef, Emilio Luque

Softw. Pract. Exp., 2012

2010

Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications.

Paola Caymes-Scutari, Anna Morajko, Tomàs Margalef, Emilio Luque

J. Parallel Distributed Comput., 2010

2007

Extending the Usability of a Dynamic Tuning Environment.

Paola Caymes-Scutari

PhD thesis, 2007

MATE: Monitoring, Analysis and Tuning Environment for parallel/distributed applications.

Anna Morajko, Paola Caymes-Scutari, Tomàs Margalef, Emilio Luque

Concurr. Comput. Pract. Exp., 2007

Automatic Generation of Dynamic Tuning Techniques.

Paola Caymes-Scutari, Anna Morajko, Tomàs Margalef, Emilio Luque

Proceedings of the Euro-Par 2007, 2007

2005

Automatic Tuning of Data Distribution Using Factoring in Master/Worker Applications.

Anna Morajko, Paola Caymes-Scutari, Tomàs Margalef, Emilio Luque

Proceedings of the Computational Science, 2005

Automatic Tuning of Master/Worker Applications.

Anna Morajko, Eduardo César, Paola Caymes-Scutari, Tomàs Margalef, Joan Sorribes, Emilio Luque

Proceedings of the Euro-Par 2005, Parallel Processing, 11th International Euro-Par Conference, Lisbon, Portugal, August 30, 2005

Development and Tuning Framework of Master/Worker Applications.

Paola Caymes-Scutari, Anna Morajko, Eduardo César, Genaro Costa, José G. Mesa, Tomàs Margalef, Joan Sorribes, Emilio Luque

Proceedings of the Automatic Performance Analysis, 12.-16. December 2005, 2005