Software Q-system for the Research of the Resource of Numerical Algorithms Parallelism

Aleeva, Valentina N.; Bogatyreva, E. A.; Skleznev, Artem; Соколов, Михаил; Shuppa, Artemii

doi:10.1007/978-3-030-36592-9_52

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…In the contrast to Hoare's model, the concept of Q-determinant [7][8][9] is not based on event communicating of processes. Parallelization and parallel execution of algorithms, taking into account the independence of operations, formed the basis of this model.…”

Section: Q-determinantmentioning

confidence: 99%

“… Determination of the most efficient implementation of the algorithm based on this concept and assessment of the complexity of this implementation;  Maximal parallelization of algorithms [8];  Determination and analysis of the parallelization resource of some algorithms (scalar product of vectors, matrix multiplication, Gauss-Jordan and Jacobi methods of solving of linear equation systems) [9];  Method of constructing a Q-determinant based on its flowchart was developed;  Method for calculating and comparing the characteristics of parallel complexity of a Q-efficient implementation of the algorithm was created [9].…”

Section: Q-determinantmentioning

confidence: 99%

“…Based on this, the main purpose of the model is to evaluate parallelism. So, to make it possible, the Software system QStudio was created [9]. It helps to evaluate a particular implementation written using the Q-determinant model.…”

Section: Q-determinantmentioning

confidence: 99%

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Asynchronous-streamed model for describing dynamically changing parallelism

Legalov¹,

Romanova²

2020

The International Workshop on Information, Computation, and Control Systems for Distributed Environments

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The article presents the concept of an asynchronous-streamed model, which is an extension of the functional data-flow model of parallel computing. We suppose that the model will be used to describe dynamically changing parallelism. This model is based on the concept of asynchronous lists, which allow considering their parallelism as an independent way of describing the parallelism of the program. The specifics of asynchronous lists are represented. Using the examples, we show how to use this model to get temporary estimates of parallelism at different conditions of solving the problem. These estimates depends on correlation between data speed getting and computation time those data in parallel devices. Also, we demonstrate how two connected asynchronous-streamed functions can form pipeline automatically. As a result, we show out that on this model it is possible to obtain temporary estimates of the calculations performed and estimations which demonstrate the levels of parallelism.

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Section: Q-determinantmentioning

confidence: 99%

Section: Q-determinantmentioning

confidence: 99%