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Frame method for solving and calculating fluid dynamics with low power consumption and high operational performance

A fluid dynamics, computing performance technology, applied in computing, processor architecture/configuration, image data processing, etc., can solve the problems of high developer requirements, time-consuming and labor-intensive

Active Publication Date: 2020-05-05
SHANGHAI UNIV
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  • Abstract
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  • Application Information

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Problems solved by technology

Therefore, the current method of using hardware description language for FPGA development is time-consuming and laborious, and the requirements for developers are too high

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  • Frame method for solving and calculating fluid dynamics with low power consumption and high operational performance
  • Frame method for solving and calculating fluid dynamics with low power consumption and high operational performance
  • Frame method for solving and calculating fluid dynamics with low power consumption and high operational performance

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Embodiment Construction

[0072] The framework for implementing high-performance computational fluid dynamics using the BLM method in an embodiment of the present invention through optimizing FPGA design will be described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the invention. It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0073] First, the CPU executes the OpenCL environment initialization and initializes the grid data according to the application parameters, and then transfers the grid data to the external memory of the FPGA.

[0074] Secondly, on the FPGA side, the data reading kernel (Read Kernel) reads the particle density distribution and boundary information data from the onboard memory, and calculates the macroscopic quantities (density, speed, etc.) corresponding to each grid, and passes...

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Abstract

The invention discloses a frame method for solving and calculating fluid dynamics with low power consumption and high operational performance, and belongs to the field of computational fluid dynamics(CFD). LBM computational fluid dynamics simulation is optimally operated at an FPGA end so as to achieve low-power-consumption high-efficiency operation. The method includes the following six steps: 1, initializing grid data and an OpenCL environment; 2, reading data and calculating macroscopic quantities such as density and speed; 3, carrying out boundary detection; 4, carrying out grid point collision calculation; 5, carrying out data dissemination; and 6, judging whether to continue or not according to an iteration stop condition, wherein the first step and the sixth step are executed at the CPU end, the other steps are executed at the FPGA end, the second step and the third step are completely parallel, and parallel calculation is also carried out in the other steps. The particle density distribution data used in the patent is stored by adopting a ping-pong caching method, so that the access of an off-chip memory is reduced.

Description

technical field [0001] The invention relates to the field of computational fluid dynamics, in particular to structure simulation and accurately solve computational fluid dynamics problems and engineering application problems through a lattice Boltzmann method. Background technique [0002] In order to accurately solve fluid mechanics problems, it is usually necessary to mesh the flow field to reach the mesoscopic simulation scale, which requires a large amount of computation and is very time-consuming, such as direct numerical simulation of turbulent flow. Nowadays, the implicit method of Navier-Stokes (N-S) equation is often used to solve large-scale algebraic equations. Although the explicit solution of Navier-Stokes (N-S) equations can avoid large-scale algebraic equations, it has better parallelism, but its The numerical stability is poor and the convergence speed is slow; while the implicit solution has good numerical stability and fast convergence speed, but its parall...

Claims

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Application Information

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IPC IPC(8): G06T1/20G06T17/20
CPCG06T1/20G06T17/20
Inventor 严伟安丁雪海童维勤支小莉程金凤
Owner SHANGHAI UNIV
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