A CPU-FPGA heterogeneous approach for biological sequence comparison using high-level synthesis (2021)
- Authors:
- Autor USP: LEJBMAN, ALFREDO GOLDMAN VEL - IME
- Unidade: IME
- DOI: 10.1002/cpe.6007
- Subjects: ALGORITMOS PARA PROCESSAMENTO; PROGRAMAÇÃO DINÂMICA
- Keywords: biological sequence comparison; dynamic programming; field-programmable gate array; high-level synthesis; longest common subsequence
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: New Jersey
- Date published: 2021
- Source:
- Título: Concurrency and Computation: Practice and Experience
- ISSN: 1532-0626
- Volume/Número/Paginação/Ano: v. 33, n. 4, art. e6007, 2021
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
JORGE, Carlos Antônio Campos et al. A CPU-FPGA heterogeneous approach for biological sequence comparison using high-level synthesis. Concurrency and Computation: Practice and Experience, v. 33, n. 4, 2021Tradução . . Disponível em: https://doi.org/10.1002/cpe.6007. Acesso em: 17 fev. 2026. -
APA
Jorge, C. A. C., Nery, A. S., Melo, A. C. M. A. de, & Goldman, A. (2021). A CPU-FPGA heterogeneous approach for biological sequence comparison using high-level synthesis. Concurrency and Computation: Practice and Experience, 33( 4). doi:10.1002/cpe.6007 -
NLM
Jorge CAC, Nery AS, Melo ACMA de, Goldman A. A CPU-FPGA heterogeneous approach for biological sequence comparison using high-level synthesis [Internet]. Concurrency and Computation: Practice and Experience. 2021 ; 33( 4):[citado 2026 fev. 17 ] Available from: https://doi.org/10.1002/cpe.6007 -
Vancouver
Jorge CAC, Nery AS, Melo ACMA de, Goldman A. A CPU-FPGA heterogeneous approach for biological sequence comparison using high-level synthesis [Internet]. Concurrency and Computation: Practice and Experience. 2021 ; 33( 4):[citado 2026 fev. 17 ] Available from: https://doi.org/10.1002/cpe.6007 - The influence of organizational factors on inter-team knowledge sharing effectiveness in agile environments
- Improving the performance of actor model runtime environments on multicore and manycore platforms
- Towards automatic actor pinning on multi-core architectures
- A simple BSP-based model to predict execution time in GPU applications
- A comparison of GPU execution time prediction using machine learning and analytical modeling
- Message from the program committee co-chairs. [Apresentação]
- Useful statistical methods for human factors research in software engineering: a discussion on validation with quantitative data
- Trying to increase the mature use of agile practices by Group Development Psychology Training: an experiment
- Scheduling moldable BSP tasks on clouds
- A multithreaded resolution of the service selection problem based on domain decomposition and work stealing
Informações sobre o DOI: 10.1002/cpe.6007 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
| 3008762.pdf | |||
| 3008762.pdf | Direct link |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
