Implementation and efficiency analysis of parallel computation using OpenACC: a case study using flow field simulations

Zhang, Shanghong; Yuan, Rui; Wu, Yu; Yang, Yi

doi:10.1080/10618562.2016.1164309

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…Since the explicit time-stepping procedure is adopted, and within a single time step the numerical mesh calculation is uncorrelated. Therefore, the loop computation on each grid can be performed in parallel (Zhang et al 2017). In this study, the hybrid MPI/OpenACC is applied to leverage multiple GPUs on a single node.…”

Section: Parallel Implementationmentioning

confidence: 99%

“…Herdman et al (2012) Clover-Leaf mini application accelerated with the OpenACC programming model, achieving a 4.91 speedup with the NVIDIA X2090 GPU over a 16-core CPU. Zhang et al (2016) the flow field case was performed using an OpenACC parallel computing application, with a speedup of 18.6 achieved by employing the NVIDIA Quadro K2000 GPU compared to a 4-core CPU. Zhang et al (2017) proposed a 2D parallel dam break model using OpenACC applications and obtained 20.7 speedups using the NVIDIA Tesla K20c GPU versus a 4-core CPU.…”

Section: Introductionmentioning

confidence: 99%

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Parallel Computation of Shallow Water Flows Using Hybrid MPI/OpenACC

Rhee

2024

Preprint

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A parallel shallow water flow model is introduced in this paper. The explicit-time finite volume approach is adopted to solve the 2D shallow water equations on an unstructured triangular mesh. The proposed scheme is second-order accurate in temporal and spatial terms using the two-stage Runge-Kutta and the monotone upwind scheme for conservation law (MUSCL) methods, respectively. Based on Message Passing Interface (MPI) and OpenACC, a multi-GPU model is presented with the METIS library to produce the domain decomposition. A CUDA-aware MPI library through GPUDirect for peer-to-peer (P2P) transfer between two GPUs and overlapping computation and MPI communication are used to speed up MPI memory exchange and the performance of the code. A 2D circular dam break test with wet and dry downstream beds and grid resolutions of about 2 million cells is considered to verify the accuracy of the code, and good results were achieved compared to the numerical simulations of published studies. Compared with the multi-CPU version of the 6-core CPU, maximum speedups of 56.18 and 331.51 were obtained using the single-GPU and multi-GPU versions, respectively. Results indicate that acceleration performance improves as the mesh resolution increases.

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Section: Parallel Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Parallel Computation of Shallow Water Flows Using Hybrid MPI/OpenACC

Rhee

2024

Preprint

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“…Lamb et al [30] reported a speedup factor of 112× for a GPU code run on a NVIDIA GeForce 8800GTX over the serial JFLOW code. Zhang et al [31,32] applied a GPU-based parallel method, OpenACC, to the parallel calculation of the flow field and the dam-break model. Rueda et al [33] performed parallel experiments on OpenACC and CUDA based on an algorithm for simulating flood storage area and on the DEM dataset of Africa.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Three Different Parallel Computation Methods for a Two‐Dimensional Dam‐Break Model

Zhang

Jing

et al. 2017

Mathematical Problems in Engineering

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Three parallel methods (OpenMP, MPI, and OpenACC) are evaluated for the computation of a two-dimensional dam-break model using the explicit finite volume method. A dam-break event in the Pangtoupao flood storage area in China is selected as a case study to demonstrate the key technologies for implementing parallel computation. The subsequent acceleration of the methods is also evaluated. The simulation results show that the OpenMP and MPI parallel methods achieve a speedup factor of 9.8× and 5.1×, respectively, on a 32-core computer, whereas the OpenACC parallel method achieves a speedup factor of 20.7× on NVIDIA Tesla K20c graphics card. The results show that if the memory required by the dam-break simulation does not exceed the memory capacity of a single computer, the OpenMP parallel method is a good choice. Moreover, if GPU acceleration is used, the acceleration of the OpenACC parallel method is the best. Finally, the MPI parallel method is suitable for a model that requires little data exchange and large-scale calculation. This study compares the efficiency and methodology of accelerating algorithms for a dam-break model and can also be used as a reference for selecting the best acceleration method for a similar hydrodynamic model.

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Hydrodynamic modeling of flash flood in mountain watersheds based on high-performance GPU computing

Song

2017

Nat Hazards

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Implementation and efficiency analysis of parallel computation using OpenACC: a case study using flow field simulations

Cited by 5 publications

References 16 publications

Parallel Computation of Shallow Water Flows Using Hybrid MPI/OpenACC

Parallel Computation of Shallow Water Flows Using Hybrid MPI/OpenACC

Comparison of Three Different Parallel Computation Methods for a Two‐Dimensional Dam‐Break Model

Hydrodynamic modeling of flash flood in mountain watersheds based on high-performance GPU computing

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