Raphael Y. de Camargo
Raphael Y. de Camargo
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A comparison of GPU execution time prediction using machine learning and analytical modeling
M Amarís, RY de Camargo, M Dyab, A Goldman, D Trystram
2016 IEEE 15th International Symposium on Network Computing and Applications …, 2016
Obtaining dynamic scheduling policies with simulation and machine learning
D Carastan-Santos, RY De Camargo
Proceedings of the International Conference for High Performance Computing …, 2017
Checkpointing-based rollback recovery for parallel applications on the integrade grid middleware
RY de Camargo, A Goldchleger, F Kon, A Goldman
Proceedings of the 2nd workshop on Middleware for grid computing, 35-40, 2004
A simple BSP-based model to predict execution time in GPU applications
M Amaris, D Cordeiro, A Goldman, RY De Camargo
2015 IEEE 22nd International Conference on High Performance Computing (HiPC …, 2015
One can only gain by replacing EASY Backfilling: A simple scheduling policies case study
D Carastan-Santos, RY De Camargo, D Trystram, S Zrigui
2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2019
Strategies for checkpoint storage on opportunistic grids
RY de Camargo, F Kon, R Cerqueira
IEEE Distributed Systems Online 7 (9), 1-1, 2006
Gene regulatory networks inference using a multi-GPU exhaustive search algorithm
FF Borelli, RY de Camargo, DC Martins, LCS Rozante
BMC bioinformatics 14, 1-12, 2013
Time experience during social distancing: A longitudinal study during the first months of COVID-19 pandemic in Brazil
AM Cravo, GB de Azevedo, C Moraes Bilacchi Azarias, LC Barne, ...
Science advances 8 (15), eabj7205, 2022
Application execution management on the InteGrade opportunistic grid middleware
FJS e Silva, F Kon, A Goldman, M Finger, RY De Camargo, F Castor Filho, ...
Journal of Parallel and Distributed Computing 70 (5), 573-583, 2010
Improving the performance of batch schedulers using online job runtime classification
S Zrigui, RY de Camargo, A Legrand, D Trystram
Journal of Parallel and Distributed Computing 164, 83-95, 2022
A multi‐GPU algorithm for large‐scale neuronal networks
RY De Camargo, L Rozante, SW Song
Concurrency and Computation: Practice and Experience 23 (6), 556-572, 2011
A common representation of time across visual and auditory modalities
LC Barne, JR Sato, RY de Camargo, PME Claessens, MS Caetano, ...
Neuropsychologia 119, 223-232, 2018
Finding exact hitting set solutions for systems biology applications using heterogeneous GPU clusters
D Carastan-Santos, RY de Camargo, DC Martins Jr, SW Song, ...
Future Generation Computer Systems 67, 418-429, 2017
Checkpointing BSP parallel applications on the InteGrade Grid middleware
RY De Camargo, A Goldchleger, F Kon, A Goldman
Concurrency and Computation: Practice and Experience 18 (6), 567-579, 2006
The Grid architectural pattern: Leveraging distributed processing capabilities
RY de Camargo, A Goldchleger, M Carneiro, F Kon
Pattern Languages of Program Design 5, 337-356, 2006
Strategies for storage of checkpointing data using non-dedicated repositories on grid systems
RY de Camargo, R Cerqueira, F Kon
Proceedings of the 3rd international workshop on Middleware for grid …, 2005
Portable checkpointing and communication for BSP applications on dynamic heterogeneous Grid environments
RY De Camargo, F Kon, A Goldman
17th International Symposium on Computer Architecture and High Performance …, 2005
Exploiting a generic approach for constructing mobile device applications
J Ueyama, VPV Pinto, ERM Madeira, P Grace, TMM Jonhson, ...
Proceedings of the Fourth International ICST Conference on COMmunication …, 2009
Design and implementation of a middleware for data storage in opportunistic grids
RY De Camargo, F Kon
Seventh IEEE International Symposium on Cluster Computing and the Grid …, 2007
Grid: An architectural pattern
RY de Camargo, A Goldchleger, M Carneiro, F Kon
The 11th Conference on Pattern Languages of Programs (PLoP’2004), 337-356, 2004
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