Meso-scale oriented simulation towards virtual process engineering (VPE)—The EMMS Paradigm

Ge, Wei; Wang, Wei; Yang, Ning; Li, Jinghai; Kwauk, Mooson; Chen, Feiguo; Chen, Jianhua; Fang, Xiaojian; Guo, Li; He, Xiaoxiao; Liu, Xinhua; Liu, Yaning; Lu, Bona; Wang, Jian; Wang, Junwu; Wang, Limin; Wang, Xiaowei; Xiong, Qingang; Xu, Minyi; Deng, Lijuan; Han, Yongsheng; Hou, Chaofeng; Hua, Leina; Huang, Wuyang; Li, Bo; Li, Chengxiang; Li, Fēi; Ren, Ying; Xu, Jianzhong; Zhang, Nan; Zhang, Yun; Zhou, Guofeng; Zhou, Guangzheng

doi:10.1016/j.ces.2011.05.029

Cited by 130 publications

(49 citation statements)

References 84 publications

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“…Because of CUDA's interoperability with OpenGL, we couple the efficient GPU implementation of the LBM with a visualization framework developed by our group [20] to realize large-scale simulations. In this section, we conduct a direct numerical simulation of gas up-flowing through 1166400 suspended solid particles under a two-dimensional doubly periodical boundary condition.…”

Section: Applicationmentioning

confidence: 99%

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Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units

Xiong

et al. 2012

Chin. Sci. Bull.

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Many-core processors, such as graphic processing units (GPUs), are promising platforms for intrinsic parallel algorithms such as the lattice Boltzmann method (LBM). Although tremendous speedup has been obtained on a single GPU compared with mainstream CPUs, the performance of the LBM for multiple GPUs has not been studied extensively and systematically. In this article, we carry out LBM simulation on a GPU cluster with many nodes, each having multiple Fermi GPUs. Asynchronous execution with CUDA stream functions, OpenMP and non-blocking MPI communication are incorporated to improve efficiency. The algorithm is tested for two-dimensional Couette flow and the results are in good agreement with the analytical solution. For both the one-and two-dimensional decomposition of space, the algorithm performs well as most of the communication time is hidden. Direct numerical simulation of a two-dimensional gas-solid suspension containing more than one million solid particles and one billion gas lattice cells demonstrates the potential of this algorithm in large-scale engineering applications. The algorithm can be directly extended to the three-dimensional decomposition of space and other modeling methods including explicit grid-based methods. asynchronous execution, compute unified device architecture, graphic processing unit, lattice Boltzmann method, non-blocking message passing interface, OpenMP Citation: Xiong Q G, Li B, Xu J, et al. Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units. Chin Sci Bull, 2012, 57: 707715, doi: 10.1007/s11434-011-4908-yHigh-performance computing (HPC) on general-purpose graphical processing units (GPGPUs) has emerged as a competitive approach to make demanding computations such as those of computational fluid dynamics (CFD) [1,2] and discrete particle simulations [3][4][5]. This is, on one hand, due to the computational capacity of graphical processing units (GPUs), which is almost one order of magnitude higher than that of mainstream central processing units (CPUs)

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Section: Applicationmentioning

confidence: 99%

“…Large-scale direct numerical simulation of a two-dimensional gas-solid suspension containing more than one million particles [20]. …”

Section: Figure 10mentioning

confidence: 99%

Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units

Xiong

et al. 2012

Chin. Sci. Bull.

Self Cite

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“…Further extensions were made to describe other more complex systems such as emulsions, granular flow, foam drainage, and gas-liquid flow [7,10], as detailed in [26]. Recently, this principle has been applied to protein folding [35], general turbulence [36] and material preparation [18], further confirming its importance and universality.…”

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confidence: 93%

“…In chemical engineering, VR is used to simulate and visualize real industrial processes on computers by solving the mathematical equations of physical models with numerical methods. This allows chemical engineers to design, scale-up, optimize or control processes online and in real time (or if not in real time, at an acceptable rate) without the need to conduct numerous experiments in multiple stages involving trial and error [10,11]. Realization of VR in chemical engineering is currently a great challenge, but also hints that a golden age of chemical engineering science [12] is to come.…”

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confidence: 99%

“…Continuing this tendency, the next step for chemical engineering should focus on real details at meso-and microscales to extract the common ''scientific principles'' from different phenomena, that is, reaction and transfer of mass, energy and momentum to allow quantitative computation of whole chemical processes and to realize VPE. The establishment of common principles will be very much subject to the progress on mesoscale phenomena between elements and systems [10,14], possibly leading to a new age of chemical engineering featuring virtual reality, intensive data and enabling material design, process quantification and system optimization from molecules to commercialization.…”

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