High-Level and Efficient Stream Parallelism on Multi-core Systems with SPar for Data Compression Applications

  • Dalvan Griebler PUCRS
  • Renato B. Hoffmann PUCRS
  • Junior Loff PUCRS
  • Marco Danelutto UNIPI
  • Luiz Gustavo Fernandes PUCRS


The stream processing domain is present in several real-world applications that are running on multi-core systems. In this paper, we focus on data compression applications that are an important sub-set of this domain. Our main goal is to assess the programmability and efficiency of domain-specific language called SPar. It was specially designed for expressing stream parallelism and it promises higher-level parallelism abstractions without significant performance losses. Therefore, we parallelized Lzip and Bzip2 compressors with SPar and compared with state-of-the-art frameworks. The results revealed that SPar is able to efficiently exploit stream parallelism as well as provide suitable abstractions with less code intrusion and code refactoring.


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GRIEBLER, Dalvan; B. HOFFMANN, Renato; LOFF, Junior; DANELUTTO, Marco; GUSTAVO FERNANDES, Luiz. High-Level and Efficient Stream Parallelism on Multi-core Systems with SPar for Data Compression Applications. In: SIMPÓSIO EM SISTEMAS COMPUTACIONAIS DE ALTO DESEMPENHO (SSCAD), 18. , 2017, Campinas. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2017 . p. 16-27. DOI: https://doi.org/10.5753/wscad.2017.235.