A comparison of GPU execution time prediction using machine learning and analytical modeling (2016)
- Authors:
- Autor USP: LEJBMAN, ALFREDO GOLDMAN VEL - IME
- Unidade: IME
- DOI: 10.1109/NCA.2016.7778637
- Subjects: COMPUTAÇÃO GRÁFICA; GEOMETRIA E MODELAGEM COMPUTACIONAL; ARQUITETURA E ORGANIZAÇÃO DE COMPUTADORES; APRENDIZADO COMPUTACIONAL
- Keywords: CUDA; Performance Predictio; BSP model; GPU Architectures
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2016
- Source:
- Título: Proceedings
- Conference titles: International Symposium on Network Computing and Applications (NCA)
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
AMARÍS, Marcos et al. A comparison of GPU execution time prediction using machine learning and analytical modeling. 2016, Anais.. Piscataway: IEEE, 2016. Disponível em: https://doi.org/10.1109/NCA.2016.7778637. Acesso em: 11 jan. 2026. -
APA
Amarís, M., Camargo, R. Y. de, Dyab, M., Goldman, A., & Trystram, D. (2016). A comparison of GPU execution time prediction using machine learning and analytical modeling. In Proceedings. Piscataway: IEEE. doi:10.1109/NCA.2016.7778637 -
NLM
Amarís M, Camargo RY de, Dyab M, Goldman A, Trystram D. A comparison of GPU execution time prediction using machine learning and analytical modeling [Internet]. Proceedings. 2016 ;[citado 2026 jan. 11 ] Available from: https://doi.org/10.1109/NCA.2016.7778637 -
Vancouver
Amarís M, Camargo RY de, Dyab M, Goldman A, Trystram D. A comparison of GPU execution time prediction using machine learning and analytical modeling [Internet]. Proceedings. 2016 ;[citado 2026 jan. 11 ] Available from: https://doi.org/10.1109/NCA.2016.7778637 - Fostering effective inter-team knowledge sharing in agile software development
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Informações sobre o DOI: 10.1109/NCA.2016.7778637 (Fonte: oaDOI API)
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