| 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 | 68 | 2016 |
| A Simple BSP-based Model to Predict Execution Time in GPU Applications M Amarís, D Cordeiro, A Goldman, RY de Camargo 22nd International Conference on High Performance Computing (HiPC), 285-294, 2015 | 38 | 2015 |
| Generic algorithms for scheduling applications on hybrid multi-core machines M Amaris, G Lucarelli, C Mommessin, D Trystram Euro-Par 2017: Parallel Processing: 23rd International Conference on …, 2017 | 26 | 2017 |
| Autotuning cuda compiler parameters for heterogeneous applications using the opentuner framework P Bruel, M Amaris, A Goldman Concurrency and Computation: Practice and Experience 29 (22), e3973, 2017 | 20 | 2017 |
| OpenMP is Not as Easy as It Appears R Gonçalves, M Amarís, T Okada, P Bruel, A Goldman 49th Hawaii International Conference on System Sciences, 5742-5751, 2016 | 18 | 2016 |
| A profile-based ai-assisted dynamic scheduling approach for heterogeneous architectures T Geng, M Amaris, S Zuckerman, A Goldman, GR Gao, JL Gaudiot International Journal of Parallel Programming 50 (1), 115-151, 2022 | 11 | 2022 |
| Generic algorithms for scheduling applications on heterogeneous platforms M Amaris, G Lucarelli, C Mommessin, D Trystram Concurrency and Computation: Practice and Experience 31 (15), e4647, 2019 | 8 | 2019 |
| Autotuning GPU Compiler Parameters Using OpenTuner P Bruel, M Amarís, A Goldman WSCAD'15 - XVI Simpósio em Sistemas Computacionais de Alto Desempenho, 13-23, 2015 | 7 | 2015 |
| Evaluating execution time predictions on gpu kernels using an analytical model and machine learning techniques M Amaris, R Camargo, D Cordeiro, A Goldman, D Trystram Journal of Parallel and Distributed Computing 171, 66-78, 2023 | 6 | 2023 |
| Green cloud computing: Challenges and opportunities D Cordeiro, E Francesquini, M Amarís, M Castro, A Baldassin, JVF Lima Anais Estendidos do XIX Simpósio Brasileiro de Sistemas de Informação, 129-131, 2023 | 5 | 2023 |
| PDAWL: profile-based iterative dynamic adaptive workload balance on heterogeneous architectures T Geng, M Amaris, S Zuckerman, A Goldman, GR Gao, JL Gaudiot Job Scheduling Strategies for Parallel Processing: 23rd International …, 2020 | 5 | 2020 |
| Medidas de similaridad de información basadas en compresión de datos M Amarís, V Martinez, P Guillén Comunicaciones en Estadística 5 (2), 169-186, 2013 | 3* | 2013 |
| Modelagem e Predição temporal de Parâmetros de Qualidade de Água usando Redes Neurais Profundas AV Anderson Almeida, Marcos Amaris, Bruno Merlin XI Workshop de Computação Aplicada à Gestão de do Meio Ambiente e Recursos …, 2020 | 2* | 2020 |
| Scheduling Moldable BSP Tasks on Clouds TK Okada, M Amarís, AG vel Lejbman Simpósio de Sistemas Computacionais de Alto Desempenho, 2015 | 1 | 2015 |
| Predição de Consumo Energético de Aplicações OpenMP em Máquinas Multi-core com Aprendizado de Máquina F Queiroz, E Damasceno, L Siqueira, M Amaris, T Rodrigues Simpósio em Sistemas Computacionais de Alto Desempenho (SSCAD), 129-136, 2024 | | 2024 |
| Performance and Energy Prediction of OpenMP and CUDA Applications using Machine Learning and Pre-execution Features F Queiroz, L Siqueira, E Damasceno, T Rodrigues, M Amaris Simpósio em Sistemas Computacionais de Alto Desempenho (SSCAD), 228-239, 2024 | | 2024 |
| Comparative Analysis of Compiler Efficiency: Energy Consumption Metrics in High-Performance Computing Domains E Damasceno, F Queiroz, L Siqueira, T Rodrigues, M Amaris Simpósio em Sistemas Computacionais de Alto Desempenho (SSCAD), 252-263, 2024 | | 2024 |
| Workflows Community Summit 2024: Future Trends and Challenges in Scientific Workflows D Bard, K Chard, S de Witt, IT Foster, C Goble, W Godoy, J Gustafsson, ... | | 2024 |
| Workflows Community Summit 2024: Future Trends and Challenges in Scientific Workflows RF Da Silva, D Bard, K Chard, S de Witt, IT Foster, T Gibbs, C Goble, ... arXiv preprint arXiv:2410.14943, 2024 | | 2024 |
| Workflows Community Summit 2024: Future Trends and Challenges in Scientific Workflows R Ferreira Da Silva, D Bard, K Chard, I Foster, T Gibbs, C Goble, W Godoy, ... Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States), 2024 | | 2024 |
Alfredo GoldmanAssociate Professor of Computer Science, University of São PauloPotvrđena adresa e-pošte na ime.usp.br
