1 resultado para arm
em Scielo Uruguai
Filtro por publicador
- Aberdeen University (1)
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- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (2)
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- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (10)
- Aston University Research Archive (3)
- B-Digital - Universidade Fernando Pessoa - Portugal (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (3)
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- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (13)
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- Center for Jewish History Digital Collections (4)
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- Scielo Uruguai (1)
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- Universidad del Rosario, Colombia (14)
- Universidad Politécnica de Madrid (1)
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- Universidade de Lisboa - Repositório Aberto (2)
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- Universidade Federal do Rio Grande do Norte (UFRN) (1)
- Universitat de Girona, Spain (2)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (2)
- Université de Lausanne, Switzerland (24)
- Université de Montréal (3)
- Université de Montréal, Canada (41)
- University of Michigan (32)
- University of Queensland eSpace - Australia (16)
Resumo:
The high performance computing community has traditionally focused uniquely on the reduction of execution time, though in the last years, the optimization of energy consumption has become a main issue. A reduction of energy usage without a degradation of performance requires the adoption of energy-efficient hardware platforms accompanied by the development of energy-aware algorithms and computational kernels. The solution of linear systems is a key operation for many scientific and engineering problems. Its relevance has motivated an important amount of work, and consequently, it is possible to find high performance solvers for a wide variety of hardware platforms. In this work, we aim to develop a high performance and energy-efficient linear system solver. In particular, we develop two solvers for a low-power CPU-GPU platform, the NVIDIA Jetson TK1. These solvers implement the Gauss-Huard algorithm yielding an efficient usage of the target hardware as well as an efficient memory access. The experimental evaluation shows that the novel proposal reports important savings in both time and energy-consumption when compared with the state-of-the-art solvers of the platform.