Towards Efficient Stream Parallelism for Embedded Devices
Resumo
Stream processing applications process raw data-flows to reveal insightful information. Efficiently coordinating the requirements of these applications is a challenge. We propose investigating high-level software solutions for these applications to achieve efficiency and high performance for embedded devices.Referências
Aldegheri, S. e. a. (2018). Enhancing performance of computer vision applications on low-power embedded systems through heterogeneous parallel programming. In IFIP.
Andrade, H. e. a. (2014). Fundamentals of Stream Processing: Application Design, Systems, and Analytics. Cambridge University Press, Cambridge.
Griebler, D. e. a. (2017). SPar: A DSL for High-Level and Productive Stream Parallelism. Parallel Processing Letters.
Lin, P. e. a. (2021). Resource management for pervasive edge computing-assisted wireless vr streaming in industrial internet of things. IEEE Transactions on Ind. Inf.
Andrade, H. e. a. (2014). Fundamentals of Stream Processing: Application Design, Systems, and Analytics. Cambridge University Press, Cambridge.
Griebler, D. e. a. (2017). SPar: A DSL for High-Level and Productive Stream Parallelism. Parallel Processing Letters.
Lin, P. e. a. (2021). Resource management for pervasive edge computing-assisted wireless vr streaming in industrial internet of things. IEEE Transactions on Ind. Inf.
Publicado
18/04/2022
Como Citar
HOFFMANN, Renato B.; GRIEBLER, Dalvan; FERNANDES, Luiz G..
Towards Efficient Stream Parallelism for Embedded Devices. In: ESCOLA REGIONAL DE ALTO DESEMPENHO DA REGIÃO SUL (ERAD-RS), 22. , 2022, Curitiba.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 63-64.
ISSN 2595-4164.
DOI: https://doi.org/10.5753/eradrs.2022.19163.
