Enhanced Parallel bzip2 Compression with Lock-Free Queue
Since the general trend nowadays is to have more and more processors (cores) available in each computer, the scalability of the data structures used in parallel programs must be carefully considered in order to guarantee that they take full advantage of the available processors. Because of increased...
| Autores: | , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2017 |
| País: | Costa Rica |
| Recursos: | Universidad Nacional de Costa Rica |
| Repositório: | Portal de Revistas UNA |
| Idioma: | inglês |
| OAI Identifier: | oai:ojs.www.una.ac.cr:article/9620 |
| Acesso em linha: | https://www.revistas.una.ac.cr/index.php/uniciencia/article/view/9620 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Computer programming Data processing Programming languages Programación informática Procesamiento de datos Lenguaje de programación. |
| Resumo: | Since the general trend nowadays is to have more and more processors (cores) available in each computer, the scalability of the data structures used in parallel programs must be carefully considered in order to guarantee that they take full advantage of the available processors. Because of increased containment, lock-based data structures usually do not perform proportionally as the number of processors increases. The use of well-designed lock-free data structures, like first in-first out, (fifo) queues, can boost the performance of a parallel program when many processors are available. In this work, a parallel version of bzip2, a popular compression and decompression program, is designed and implemented by using lock-free queues instead of the lock-based ones, and applying a two-buffer-output strategy. The performance of lock-free implementation is measured against lock-based implementations. Compression time was measured with different number of processors and different block sizes. Consistent with our hypothesis, the results show that our parallel lock-free implementation outperforms the other implementations. |
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