Towards Efficient Stream Parallelism for Embedded Devices

  • Renato B. Hoffmann PUCRS
  • Dalvan Griebler PUCRS
  • Luiz G. Fernandes PUCRS


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.


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.
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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: