A highly optimized skeleton for unbalanced and deep divide-and-conquer algorithms on multi-core clusters

Martínez, Millán A.; Fraguela, Basilio B.; Dominguez, Jessica A.

doi:10.1007/s11227-021-04259-5

Cited by 4 publications

(2 citation statements)

References 28 publications

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“…When distributed memory is used, data communication adds an important overhead, that should be optimized through data packaging, data serialization, or by combing reading with data distribution, or/and data aggregation with data writing. Examples of frameworks that treat these problems are those reported in [44,45].…”

Section: Synchronization and Data Managementmentioning

confidence: 99%

On Generalizing Divide and Conquer Parallel Programming Pattern

Niculescu¹

2022

Mathematics

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(1) Background: Structuring is important in parallel programming in order to master its complexity, and this structuring could be achieved through programming patterns and skeletons. Divide-and-conquer computation is essentially defined by a recurrence relation that links the solution of a problem to the solutions of subproblems of the same type, but of smaller sizes. This pattern allows the specification of different types of computations, and so it is important to provide a general specification that comprises all its cases. We intend to prove that the divide-and-conquer pattern could be generalized such that to comprise many of the other parallel programming patterns, and in order to prove this, we provide a general formulation of it. (2) Methods: Starting from the proposed generalized specification of the divide-and-conquer pattern, the computation of the pattern is analyzed based on its stages: decomposition, base-case and composition. Examples are provided, and different execution models are analyzed. (3) Results: a general functional specification is provided for a divide-and-conquer pattern and based on it, and we prove that this general formulation could be specialized through parameters’ instantiating into other classical parallel programming patterns. Based on the specific stages of the divide-and-conquer, three classes of computations are emphasized. In this context, an equivalent efficient bottom-up computation is formally proved. Associated models of executions are emphasized and analyzed based on the three classes of divide-and-conquer computations. (4) Conclusion: A more general definition of the divide-and-conquer pattern is provided, and this includes an arity list for different decomposition degrees, a level of recursion, and also an alternative solution for the cases that are not trivial but allow other approaches (sequential or parallel) that could lead to better performance. Together with the associated analysis of patterns equivalence and optimized execution models, this provides a general formulation that is useful both at the semantic level and implementation level.

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Section: Synchronization and Data Managementmentioning

confidence: 99%

On Generalizing Divide and Conquer Parallel Programming Pattern

Niculescu¹

2022

Mathematics

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“…Além disso, encontrar uma amostra representativa de participantes experientes no domínio da programac ¸ão paralela é desafiador. Logo, o uso de métricas de codificac ¸ão bem estabelecidas na área de Engenharia de Software (e.g., Linhas de Código (LOC), Halstead e Constructive Cost Model -COCOMO) pode facilitar a avaliac ¸ão da produtividade [Adornes et al 2015, Griebler et al 2018, Miller et al 2018, Rodriguez-Canal et al 2021, Martínez et al 2022, Peccerillo e Bartolini 2022. Porém, nosso estudo anterior [Andrade et al 2021] mostrou limitac ¸ões, uma vez que estas métricas de codificac ¸ão não foram projetados para avaliar aplicac ¸ões paralelas.…”

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Opinião de Brasileiros Sobre a Produtividade no Desenvolvimento de Aplicações Paralelas

Andrade

Griebler²,

Santos³

et al. 2022

Anais Do XXIII Simpósio Em Sistemas Computacionais De Alto Desempenho (SSCAD 2022)

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A partir da popularização das arquiteturas paralelas, surgiram várias interfaces de programação a fim de facilitar a exploração de tais arquiteturas e aumentar a produtividade dos desenvolvedores. Entretanto, desenvolver aplicações paralelas ainda é uma tarefa complexa para desenvolvedores com pouca experiência. Neste trabalho, realizamos uma pesquisa para descobrir a opinião de desenvolvedores de aplicações paralelas sobre os fatores que impedem a produtividade. Nossos resultados mostraram que a experiência dos desenvolvedores é uma das principais razões para a baixa produtividade. Além disso, os resultados indicaram formas para contornar este problema, como melhorar e incentivar o ensino de programação paralela em cursos de graduação.

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