Submitted by PPG Ci?ncia da Computa??o (ppgcc@pucrs.br) on 2018-08-22T17:39:55Z No. of bitstreams: 1 ADRIANO_JOS?_VOGEL_DIS.pdf: 2344216 bytes, checksum: e0dd6229d4a98c039e793851290beab0 (MD5) / Approved for entry into archive by Sheila Dias (sheila.dias@pucrs.br) on 2018-08-24T14:50:33Z (GMT) No. of bitstreams: 1 ADRIANO_JOS?_VOGEL_DIS.pdf: 2344216 bytes, checksum: e0dd6229d4a98c039e793851290beab0 (MD5) / Made available in DSpace on 2018-08-24T17:31:58Z (GMT). No. of bitstreams: 1 ADRIANO_JOS?_VOGEL_DIS.pdf: 2344216 bytes, checksum: e0dd6229d4a98c039e793851290beab0 (MD5) Previous issue date: 2018-03-28 / As aplica??es de stream se tornaram cargas de trabalho representativas nos sistemas computacionais. Diversos dom?nios de aplica??es representam stream, como v?deo, ?udio, processamento de gr?ficos e imagens. Uma parcela significativa dessas aplica??es demanda paralelismo para aumentar o desempenho. Por?m, programadores frequentemente enfrentam desafios entre produtividade de c?digo e desempenho devido ?s complexidades decorrentes do paralelismo. Buscando facilitar a paraleliza??o, a DSL SPar foi criada usando atributos (stage, input, output, and replicate) do C++-11 para representar paralelismo. O compilador reconhece os atributos da SPar e gera c?digo paralelo automaticamente. Um desafio relevante que ocorre em est?gios paralelos da SPar ? a demanda pela defini??o manual do grau de paralelismo, o que consome tempo e pode induzir a erros. O grau de paralelismo ? definido atrav?s do n?mero de r?plicas em est?gios paralelos. Por?m, a execu??o de diversas aplica??es pode ser pouco eficiente se executadas com um n?mero de r?plicas inadequado ou usando um n?mero est?tico que ignora a natureza din?mica de algumas aplica??es. Para resolver esse problema, ? introduzido o conceito de um n?mero de r?plicas transparente e adaptativo para a SPar. Al?m disso, os mecanismos implementados e as regras de transforma??o s?o descritos para possibilitar a gera??o de c?digo paralelo na SPar com um n?mero adaptativo de r?plicas. Os mecanismos adaptativos foram avaliados demonstrando a sua efic?cia. Ainda, aplica??es reais foram usadas para demonstrar que os mecanismos adaptativos propostos podem oferecer abstra??es de alto n?vel sem significativas perdas de desempenho. / In recent years, stream processing applications have become a traditional workload in computing systems. They are traditionally found in video, audio, graphic and image processing. Many of these applications demand parallelism to increase performance. However, programmers must often face the trade-off between coding productivity and performance that introducing parallelism creates. SPar Domain-Specific Language (DSL) was created to achieve the optimal balance for programmers, with the C++-11 attribute annotation mechanism to ensure that essential properties of stream parallelism could be represented (stage, input, output, and replicate). The compiler recognizes the SPar attributes and generates parallel code automatically. The need to manually define parallelism is one crucial challenge for increasing SPAR?s abstraction level, because it is time consuming and error prone. Also, executing several applications can fail to be efficient when running a non suitable number of replicas. This occurs when the defined number of replicas in a parallel region is not optimal or when a static number is used, which ignores the dynamic nature of stream processing applications. In order to solve this problem, we introduced the concept of the abstracted and adaptive number of replicas for SPar. Moreover, we described our implemented strategy as well as transformation rules that enable SPar to generate parallel code with the adaptive degree of parallelism support. We experimentally evaluated the implemented adaptive strategies regarding their effectiveness. Thus, we used real-world applications to demonstrate that our adaptive strategy implementations can provide higher abstraction levels without significant performance degradation.