High-Level and Efficient Stream Parallelism on Multi-core Systems with SPar for Data Compression Applications
Resumo
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 re-factoring.
Publicado
2018-03-28
Como Citar
GRIEBLER, Dalvan Griebler et al.
High-Level and Efficient Stream Parallelism on Multi-core Systems with SPar for Data Compression Applications.
Teste, [S.l.], mar. 2018.
Disponível em: <http://143.54.25.88/index.php/teste/article/view/773>. Acesso em: 19 sep. 2024.
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