Marcos Amaris
Title
Cited by
Cited by
Year
A comparison of GPU execution time prediction using machine learning and analytical modeling
M Amaris, RY de Camargo, M Dyab, A Goldman, D Trystram
2016 IEEE 15th International Symposium on Network Computing and Applications …, 2016
362016
Generic algorithms for scheduling applications on hybrid multi-core machines
M Amaris, G Lucarelli, C Mommessin, D Trystram
European Conference on Parallel Processing, 220-231, 2017
252017
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
252015
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
162016
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
112017
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
52019
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
42015
PDAWL: Profile-based Iterative Dynamic Adaptive WorkLoad Balance on Heterogeneous Architectures
T Geng, M Amaris, S Zuckerman, A Goldman, GR Gao, JL Gaudiot
Workshop on Job Scheduling Strategies for Parallel Processing, 145-162, 2020
22020
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
1*2020
Scheduling Moldable BSP Tasks on Clouds
TK Okada, M Amarís, AG vel Lejbman
Simpósio de Sistemas Computacionais de Alto Desempenho, 2015
12015
Predição temporal de parâmetros da qualidade da água usando redes neurais profundas Temporal prediction of water quality parameters using deep neural networks
AF de Sousa Almeida, AA de Oliveira Veras, B Merlin, A Santos, M Amaris
Brazilian Journal of Development 7 (11), 107662-107678, 2021
2021
Efficient Prediction of Region-wide Traffic States in Public Bus Networks using LSTMs
M Amaris, MA Morais, RY De Camargo
2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021
2021
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, 1-37, 2021
2021
Performance Prediction Modeling of GPU Applications
M Amarís, RY de Camargo, A Goldman
2017
Medidas de similaridad de información basadas en compresión de datos
M Amarís, V Martinez, P Guillén
Comunicaciones en Estadística 5 (2), 169-186, 2013
2013
Máquinas de Aprendizaje No Supervisadas para la Clasificación de Senales Electrocardiográficas
M Amarís, V Martinez, P Guillén
8th International Seminar on Medical Information Processing and Analysis, 2012
2012
Aplicación de Software para la Clasificación de Senales Electrocardiográficas de Infarto Agudo de Miocardio Implementando
V Amarís González, Marcos. Martinez Abaunza
University of Santander - Colombia 19 (370), 2012
2012
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Articles 1–17