Faaster, better, cheaper: The prospect of serverless scientific computing and hpc J Spillner, C Mateos, DA Monge Latin American High Performance Computing Conference, 154-168, 2017 | 132 | 2017 |
Reinforcement learning-based application autoscaling in the cloud: A survey Y Garí, DA Monge, E Pacini, C Mateos, CG Garino Engineering Applications of Artificial Intelligence 102, 104288, 2021 | 89 | 2021 |
A Comparative Analysis of NSGA‐II and NSGA‐III for Autoscaling Parameter Sweep Experiments in the Cloud V Yannibelli, E Pacini, D Monge, C Mateos, G Rodriguez Scientific Programming 2020 (1), 4653204, 2020 | 35 | 2020 |
CMI: An online multi-objective genetic autoscaler for scientific and engineering workflows in cloud infrastructures with unreliable virtual machines DA Monge, E Pacini, C Mateos, E Alba, CG Garino Journal of Network and Computer Applications 149, 102464, 2020 | 27 | 2020 |
Ensemble learning of runtime prediction models for gene-expression analysis workflows DA Monge, M Holec, F Železný, CG Garino Cluster Computing 18, 1317-1329, 2015 | 25 | 2015 |
Meta-heuristic based autoscaling of cloud-based parameter sweep experiments with unreliable virtual machines instances DA Monge, E Pacini, C Mateos, CG Garino Computers & Electrical Engineering 69, 364-377, 2018 | 20 | 2018 |
Autoscaling Scientific Workflows on the Cloud by Combining On-demand and Spot Instances. DA Monge, Y Garí, C Mateos, CG Garino Computer Systems Science & Engineering 32 (4), 2017 | 20 | 2017 |
Sensibilidad de resultados del ensayo de tracción simple frente a diferentes tamaños y tipos de imperfecciones C Careglio, D Monge, E Pacini, C Mateos, A Mirasso, CG Garino Mecánica Computacional 29 (41), 4181-4197, 2010 | 19 | 2010 |
Learning budget assignment policies for autoscaling scientific workflows in the cloud Y Garí, DA Monge, C Mateos, C García Garino Cluster Computing 23, 87-105, 2020 | 16 | 2020 |
Adaptive spot-instances aware autoscaling for scientific workflows on the cloud DA Monge, C García Garino Latin American High Performance Computing Conference, 13-27, 2014 | 16 | 2014 |
A Q-learning approach for the autoscaling of scientific workflows in the Cloud Y Garí, DA Monge, C Mateos Future Generation Computer Systems 127, 168-180, 2022 | 13 | 2022 |
A performance comparison of data-aware heuristics for scheduling jobs in mobile grids M Hirsch, C Mateos, JM Rodriguez, A Zunino, Y Garí, DA Monge 2017 XLIII Latin American Computer Conference (CLEI), 1-8, 2017 | 11 | 2017 |
Ensemble learning of run-time prediction models for data-intensive scientific workflows DA Monge, M Holec, F Z̆elezný, C García Garino High Performance Computing: First HPCLATAM-CLCAR Latin American Joint …, 2014 | 8 | 2014 |
A performance prediction module for workflow scheduling DA Monge, J Bělohradský, C García Garino, F Železný IV High-Performance Computing Symposium (HPC 2011)(XL JAIIO, Córdoba, 31 de …, 2011 | 7 | 2011 |
Online rl-based cloud autoscaling for scientific workflows: Evaluation of q-learning and sarsa Y Garí, E Pacini, L Robino, C Mateos, DA Monge Future Generation Computer Systems 157, 573-586, 2024 | 6 | 2024 |
Markov decision process to dynamically adapt spots instances ratio on the autoscaling of scientific workflows in the cloud Y Garí, DA Monge, C Mateos, C García Garino High Performance Computing: 4th Latin American Conference, CARLA 2017 …, 2018 | 6 | 2018 |
Improving Workflows Execution on DAGMan by a Perfomance-driven Scheduling Tool DA Monge, C García Garino High-Performance Computing Symposium (HPC 2010)-JAIIO 39 (UADE, 30 de agosto …, 2010 | 5 | 2010 |
Logos: Enabling local resource managers for the efficient support of data-intensive workflows within grid sites DA Monge, CG Garino Computing and Informatics 33 (1), 109-130, 2014 | 4 | 2014 |
Computational mechanics software as a service project C García Garino, ER Pacini Naumovich, DA Monge Bosdari, CA Careglio, ... ISTEC, 2013 | 4 | 2013 |
Template-based semi-automatic workflow construction for gene expression data analysis J Bělohradský, D Monge, F Železný, M Holec, CG Garino 2011 24th International Symposium on Computer-Based Medical Systems (CBMS), 1-6, 2011 | 3 | 2011 |