Towards efficient GPGPU Cellular Automata model implementation using persistent active cells

Renc, Paweł; Pęcak, Tomasz; Rango, Alessio De; Spataro, William; Mendicino, Giuseppe; Wăs, Jarosław

doi:10.1016/j.jocs.2021.101538

Cited by 11 publications

(4 citation statements)

References 34 publications

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“…The GPGPU paradigm enables an efficient parallel execution of CA models by assigning each cell to a different GPGPU thread ( [21]). The CA space domain is initially transferred from the host memory to the device (global) memory.…”

Section: Gpgpu Executionmentioning

confidence: 99%

OpenCAL++: An object-oriented architecture for transparent Parallel Execution of Cellular Automata models

Giordano

D'Ambrosio

Macrì

et al. 2023

2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)

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Cellular Automata (CA) models, initially studied by John von Neumann, have been developed by numerous researchers and applied in both academic and scientific fields. Thanks to their local and independent rules, simulations of complex systems can be easily implemented based on CA modelling on parallel machines. However, due to the heterogeneity of the components -from the hardware to the software perspective-the various possible scenarios running parallelism in today's architectures can pose a challenge in such implementations, making it difficult to exploit. This paper presents OpenCAL++, a transparent and efficient object-oriented platform for the parallel execution of cellular automata models. The architecture of OpenCAL++ ensures the modeller a fully transparent parallel execution and a strong "separation of concerns" between the execution parallelism issues and the model implementation. The code implementing the Cellular Automata model remains the same whether the execution performs in a shared-, distributed-memory or a GPGPU context, irrespective of the optimizations adopted. To this aim, the object-oriented paradigm has been intensely exploited. As well as the OpenCAL++ architecture, we present the description of a simple Cellular Automata model implementation for illustrative purposes.

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Section: Gpgpu Executionmentioning

confidence: 99%

OpenCAL++: An object-oriented architecture for transparent Parallel Execution of Cellular Automata models

Giordano

D'Ambrosio

Macrì

et al. 2023

2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)

Self Cite

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“…In the scientific literature, a lot of works with different parallelization techniques can be found in the area of CA calculations. In general, they can be divided into three main groups: 1) CPU (central processing unit) based computations, [149] 2) GPU (graphical processor unit) based computations, [150,151] and 3) heterogeneous platform computations. [152] The first group of approaches based on CPU parallelization is directed at the division of a large computational problem into a As shown in Figure 11, when a single computing unit is considered, the maximum number of threads used during simulation should equal the number of available processor cores.…”

Section: High-performance Ca Models Of Static Recrystallizationmentioning

confidence: 99%

Section: High‐performance Ca Models Of Static Recrystallizationmentioning

confidence: 99%

Computationally Efficient Cellular Automata‐Based Full‐Field Models of Static Recrystallization: A Perspective Review

Madej

Sitko

2022

steel research int.

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The evolution of metallic material microstructures under thermomechanical treatment is a critical element that influences the in‐use properties of the final product. In the last four decades, many researchers around the world focused on reliable numerical recreation of phenomena that occur during metal processing. Particular attention is put on the phase transformation, texture evolution, and recrystallization predictions to simulate material behavior at the subsequent processing stages. In recent years, approaches taking into account explicit representation of morphological elements during simulation are becoming more frequently used even at the industrial scale. One of those methods addressed within the current article in application to static recrystallization (SRX) modeling is the cellular automata (CA) approach. A review of the CA‐based full‐field SRX models highlights the progress in capabilities of developed approaches in consideration of various mechanisms controlling microstructure evolution like heterogeneous energy distribution, probabilistic or physics‐based nucleation, grain growth driven by different driving forces, or grain boundary migration is presented within the article. The issue of the computational time associated with 3D CA modeling is particularly addressed. Possible approaches to reducing simulation times based on efficient use of modern computer architecture are finally evaluated as guidelines for further model development.

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“…Cellular automata (CA) have proven their suitability for systems whose behaviour can be described in terms of local interactions [1]. CA were studied by John von Neumann to study self-reproduction problems [2] and have been developed by numerous researchers and applied in both theoretical and scientific fields ( [3][4][5][6][7][8]). Due to their local and independent rules, complex systems simulations can be easily implemented on parallel machines.…”

Section: Introductionmentioning

confidence: 99%

Tailoring load balancing of cellular automata parallel execution to the case of a two-dimensional partitioned domain

et al. 2023

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In this paper, techniques for dynamic load balancing of the cellular automata parallel execution are presented for the case of domain space partitioned along two dimensions. Starting from general closed-form expressions that allow to compute the optimal workload assignment in a dynamic fashion when partitioning takes place along only one dimension, we tailor the procedure to allow partitioning and balancing along both dimensions. Both qualitative and quantitative experiments are carried out that assess performance improvement in applying load balancing for the case of two-dimensional partitioned domain, especially when the load balancing takes place along both dimensions.

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Towards efficient GPGPU Cellular Automata model implementation using persistent active cells

Cited by 11 publications

References 34 publications

OpenCAL++: An object-oriented architecture for transparent Parallel Execution of Cellular Automata models

OpenCAL++: An object-oriented architecture for transparent Parallel Execution of Cellular Automata models

Computationally Efficient Cellular Automata‐Based Full‐Field Models of Static Recrystallization: A Perspective Review

Tailoring load balancing of cellular automata parallel execution to the case of a two-dimensional partitioned domain

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