Exploring simplicity and efficiency: regression-based scheduling heuristics in HPC (2023)
- Authors:
- USP affiliated authors: LEJBMAN, ALFREDO GOLDMAN VEL - IME ; ROSA, LUCAS DE SOUSA - IME
- Unidade: IME
- DOI: 10.5753/eradsp.2023.232635
- Subjects: PROGRAMAÇÃO PARALELA; APRENDIZADO COMPUTACIONAL; HEURÍSTICA
- Language: Inglês
- Imprenta:
- Publisher: SBC
- Publisher place: Porto Alegre
- Date published: 2023
- Source:
- Título do periódico: Anais
- Conference titles: Escola Regional de Alto Desempenho de São Paulo - ERAD-SP
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: bronze
-
ABNT
ROSA, Lucas de Sousa e CARASTAN-SANTOS, Danilo e GOLDMAN, Alfredo. Exploring simplicity and efficiency: regression-based scheduling heuristics in HPC. 2023, Anais.. Porto Alegre: SBC, 2023. Disponível em: https://doi.org/10.5753/eradsp.2023.232635. Acesso em: 24 jul. 2024. -
APA
Rosa, L. de S., Carastan-Santos, D., & Goldman, A. (2023). Exploring simplicity and efficiency: regression-based scheduling heuristics in HPC. In Anais. Porto Alegre: SBC. doi:10.5753/eradsp.2023.232635 -
NLM
Rosa L de S, Carastan-Santos D, Goldman A. Exploring simplicity and efficiency: regression-based scheduling heuristics in HPC [Internet]. Anais. 2023 ;[citado 2024 jul. 24 ] Available from: https://doi.org/10.5753/eradsp.2023.232635 -
Vancouver
Rosa L de S, Carastan-Santos D, Goldman A. Exploring simplicity and efficiency: regression-based scheduling heuristics in HPC [Internet]. Anais. 2023 ;[citado 2024 jul. 24 ] Available from: https://doi.org/10.5753/eradsp.2023.232635 - On limits of machine learning techniques in the learning ofscheduling policies
- An experimental analysis of regression-obtained HPC scheduling heuristics
- In search of efficient scheduling heuristics from simulations and machine learning
- Approximating the discrete resource sharing scheduling problem
- Introdução à computação heterogênea
- Useful statistical methods for human factors research in software engineering: a discussion on validation with quantitative data
- Thematic series on service composition for the future internet
- A multithreaded resolution of the service selection problem based on domain decomposition and work stealing
- Improving the performance of actor model runtime environments on multicore and manycore platforms
- Group-development psychology training: the perceived effects on agile software-development teams
Informações sobre o DOI: 10.5753/eradsp.2023.232635 (Fonte: oaDOI API)
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