Antonio Tadeu Gomes - Academia.edu (original) (raw)
Uploads
Papers by Antonio Tadeu Gomes
arXiv (Cornell University), Jul 15, 2022
HAL (Le Centre pour la Communication Scientifique Directe), Sep 9, 2020
arXiv (Cornell University), Aug 4, 2011
HAL (Le Centre pour la Communication Scientifique Directe), Dec 21, 2022
arXiv (Cornell University), Jun 4, 2022
2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)
Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOMW'06)
ArXiv, 2017
The family of Multiscale Hybrid-Mixed (MHM) finite element methods has received considerable atte... more The family of Multiscale Hybrid-Mixed (MHM) finite element methods has received considerable attention from the mathematics and engineering community in the last few years. The MHM methods allow solving highly heterogeneous problems on coarse meshes while providing solutions with high-order precision. It embeds independent local problems which are responsible for upscaling unresolved scales into the numerical solution. These local contributions are brought together through a global problem defined on the skeleton of the coarse partition. Since the local problems are completely independent, they can be easily computed in parallel. In this paper, we present two simulator prototypes specifically crafted for the MHM methods, which adopt two different implementation strategies: (i) a multi-programming language approach, each language tackling different simulation issues; and (ii) a classical, single-programming language approach. Specifically, we use C++ for numerical computation of the ...
Concurrency and Computation: Practice and Experience, 2019
SummaryWorkload‐aware loop schedulers were introduced to deliver better performance than classica... more SummaryWorkload‐aware loop schedulers were introduced to deliver better performance than classical loop scheduling strategies. However, they presented limitations such as inflexible built‐in workload estimators and suboptimal chunk scheduling. Targeting these challenges, we proposed previously a workload‐aware scheduling strategy called BinLPT, which relies on three features: (i) user‐supplied estimations of the workload of the loop; (ii) a greedy heuristic that adaptively partitions the iteration space in several chunks; and (iii) a scheduling scheme based on the Longest Processing Time (LPT) rule and on‐demand technique. In this paper, we present two new contributions to the state‐of‐the‐art. First, we introduce a multiloop support feature to BinLPT, which enables the reuse of estimations across loops. Based on this feature, we integrated BinLPT into a real‐world elastodynamics application, and we evaluated it running on a supercomputer. Second, we present an evaluation of BinLPT ...
ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240)
Journal of Communication and Information Systems, 2003
Anais do Simpósio em Sistemas Computacionais de Alto Desempenho (WSCAD)
A memory allocation anomaly occurs when the allocation of a set of heap blocks imposes an unneces... more A memory allocation anomaly occurs when the allocation of a set of heap blocks imposes an unnecessary overhead on the execution of an application. In this paper, we propose a method for identifying, locating, characterizing and fixing allocation anomalies, and a tool for developers to apply the method. We experiment our method and tool with a numerical simulator aimed at approximating the solutions to partial differential equations using a finite element method. We show that taming allocation anomalies in this simulator reduces the memory footprint of its processes by 37.27% and the execution time by 16.52%. We conclude that the developer of high-performance computing applications can benefit from the method and tool during the software development cycle.
Anais do XXXVII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2019)
O crescimento no volume dos dados tem revolucionado os negócios e a ciência ao mesmo tempo que de... more O crescimento no volume dos dados tem revolucionado os negócios e a ciência ao mesmo tempo que demanda capacidade cada vez maior dos recursos computacionais. As plataformas de computação de alto desempenho (HPC), tradicionalmente empregadas em simulações numéricas massivamente paralelas, oferecem capacidade computacional que pode ser aproveitada na análise de Big Data. No entanto, a convergência de Big Data e HPC deve ser examinada sob vários aspectos; em particular, a infraestrutura de rede precisa ajustar-se a demandas de aplicações bem distintas. O modelo de rede definida por software (SDN) pode favorecer essa convergência, graças à sua visão global da rede e sua programabilidade. Nesse contexto, apresentamos uma plataforma SDN capaz de suprir, de forma convergente, os requisitos de aplicações Big Data e HPC. A plataforma aplica mecanismos de roteamento mais adequados a cada perfil de tráfego, permitindo assim a redução no tempo de execução de aplicações. Demonstramos por meio de...
Proceedings of the XXXVIII Iberian Latin American Congress on Computational Methods in Engineering
Concurrency and Computation: Practice and Experience
arXiv (Cornell University), Jul 15, 2022
HAL (Le Centre pour la Communication Scientifique Directe), Sep 9, 2020
arXiv (Cornell University), Aug 4, 2011
HAL (Le Centre pour la Communication Scientifique Directe), Dec 21, 2022
arXiv (Cornell University), Jun 4, 2022
2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)
Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOMW'06)
ArXiv, 2017
The family of Multiscale Hybrid-Mixed (MHM) finite element methods has received considerable atte... more The family of Multiscale Hybrid-Mixed (MHM) finite element methods has received considerable attention from the mathematics and engineering community in the last few years. The MHM methods allow solving highly heterogeneous problems on coarse meshes while providing solutions with high-order precision. It embeds independent local problems which are responsible for upscaling unresolved scales into the numerical solution. These local contributions are brought together through a global problem defined on the skeleton of the coarse partition. Since the local problems are completely independent, they can be easily computed in parallel. In this paper, we present two simulator prototypes specifically crafted for the MHM methods, which adopt two different implementation strategies: (i) a multi-programming language approach, each language tackling different simulation issues; and (ii) a classical, single-programming language approach. Specifically, we use C++ for numerical computation of the ...
Concurrency and Computation: Practice and Experience, 2019
SummaryWorkload‐aware loop schedulers were introduced to deliver better performance than classica... more SummaryWorkload‐aware loop schedulers were introduced to deliver better performance than classical loop scheduling strategies. However, they presented limitations such as inflexible built‐in workload estimators and suboptimal chunk scheduling. Targeting these challenges, we proposed previously a workload‐aware scheduling strategy called BinLPT, which relies on three features: (i) user‐supplied estimations of the workload of the loop; (ii) a greedy heuristic that adaptively partitions the iteration space in several chunks; and (iii) a scheduling scheme based on the Longest Processing Time (LPT) rule and on‐demand technique. In this paper, we present two new contributions to the state‐of‐the‐art. First, we introduce a multiloop support feature to BinLPT, which enables the reuse of estimations across loops. Based on this feature, we integrated BinLPT into a real‐world elastodynamics application, and we evaluated it running on a supercomputer. Second, we present an evaluation of BinLPT ...
ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240)
Journal of Communication and Information Systems, 2003
Anais do Simpósio em Sistemas Computacionais de Alto Desempenho (WSCAD)
A memory allocation anomaly occurs when the allocation of a set of heap blocks imposes an unneces... more A memory allocation anomaly occurs when the allocation of a set of heap blocks imposes an unnecessary overhead on the execution of an application. In this paper, we propose a method for identifying, locating, characterizing and fixing allocation anomalies, and a tool for developers to apply the method. We experiment our method and tool with a numerical simulator aimed at approximating the solutions to partial differential equations using a finite element method. We show that taming allocation anomalies in this simulator reduces the memory footprint of its processes by 37.27% and the execution time by 16.52%. We conclude that the developer of high-performance computing applications can benefit from the method and tool during the software development cycle.
Anais do XXXVII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2019)
O crescimento no volume dos dados tem revolucionado os negócios e a ciência ao mesmo tempo que de... more O crescimento no volume dos dados tem revolucionado os negócios e a ciência ao mesmo tempo que demanda capacidade cada vez maior dos recursos computacionais. As plataformas de computação de alto desempenho (HPC), tradicionalmente empregadas em simulações numéricas massivamente paralelas, oferecem capacidade computacional que pode ser aproveitada na análise de Big Data. No entanto, a convergência de Big Data e HPC deve ser examinada sob vários aspectos; em particular, a infraestrutura de rede precisa ajustar-se a demandas de aplicações bem distintas. O modelo de rede definida por software (SDN) pode favorecer essa convergência, graças à sua visão global da rede e sua programabilidade. Nesse contexto, apresentamos uma plataforma SDN capaz de suprir, de forma convergente, os requisitos de aplicações Big Data e HPC. A plataforma aplica mecanismos de roteamento mais adequados a cada perfil de tráfego, permitindo assim a redução no tempo de execução de aplicações. Demonstramos por meio de...
Proceedings of the XXXVIII Iberian Latin American Congress on Computational Methods in Engineering
Concurrency and Computation: Practice and Experience