Liyang Xu

A Hybrid Decomposition Parallel Algorithm for Multi-scale Simulation of Viscoelastic Fluids

The method of Brownian configuration fields (BCF) is a promising multi-scale approach for the simulationof viscoelastic fluids, however, it is a computationally expensive method, which restricts its application in complex scenarios. Therefore, it is of great importance to optimize the parallel implementation in order to improve computational efficiency. In this paper we propose a hybrid decomposition parallel algorithm named: MCDPar, whichenables the simulation problem to bedecomposed simultaneously over mesh cells andthe Brownian configuration fields. Compution processes are split into multiple groups and Brownian configuration fields are equally associated with these groups. Meanwhile, within each group the processes are concurrently executed based on the traditional mesh decomposition approach. Finally we implemented the MCDPar algorithm in a micro-macro numerical solver based on OpenFOAM. Experimental results show that the micro-macro simulation time of viscoelastic fluids issignificantly reduced with improved scalability and parallel efficiency. In the test case with Nf = 2000 and Ncell = 262144, the speedup of the MCDParis up to 9.23x with a 7.5x increase in number of cores compared to the original parallel algorithm.

The way to develop software towards exascale computing

This paper preliminarily discusses how to develop software towards exascale computing. Two typical development models are studied, one is “all-round contract” which means all the functional modules are implemented in a single framework, and the other is “co-design” which using the existing packages to realize functional modules. As a widely used CFD software whose numerical solving module is implemented in a typical “all-round contract” manner, OpenFOAM is concerned in this work. After redesigning and reimplementing the solving module of OpenFOAM in a “co-design” way by inserting PETSc, the source lines of the code decrease dramatically, which improves the development efficiency. Tests of two CFD benchmark cases and a practical large-scale case on a 128-node cluster show that the newly implemented numerical module also has a higher solving efficiency, compared with the original numerical module in OpenFOAM. Therefore, it is recommended to develop software in a “co-design” manner towards exascale computing, and softwares already implemented in “all-round contract” way should also be reconsidered.

A Hybrid Parallel Algorithm for Solving Eeuler Equation Using Explicit RKDG Method Based on OpenFOAM

OpenFOAM is a framework of the open source C CFD toolbox for flexible engineering simulation, which uses finite volume method (FVM) in the discretization of partial differential equations (PDEs). The problem solving procedure in OpenFOAM consists in equations dicretization stage, equations solving stage and field limiting stage. The best parallelism is limited by the equation solving stage, which contains communications. Compared to FVM, discontinuous Galerkin (DG) method is a high-order discretization method, which can accelerate the convergence of the residuals over same mesh scale and has higher resolution of the flow. Based on OpenFOAM with DG method, the ratio of overhead in equations discretization stage increases, especially when solving Euler equations using an explicit method. The equations discretization stage has a better potential parallelism than the other two stages due to no existence of communication. In this paper, we will analysis the difference of time cost in these three stages between original OpenFOAM and OpenFOAM with DG method. By decoupling these three stages, a hybrid parallel algorithm for solving PDEs is proposed and implemented based on OpenFOAM with DG method. The experimental results show that the simulation time is reduced by 16%, and the relative speedup of the hybrid parallel algorithm is up to 2.88 compared to the original parallel algorithm with the same degree of parallelism.

The Curve Boundary Design and Performance Analysis for DGM Based on OpenFOAM

OpenFOAM is a widely used numerical simulation software, and Discontinuous Galerkin method (DGM), a high-order numerical method, has been developed on OpenFOAM. In order to obtain meaningful numerical simulations, curve boundary is needed, but it has not been implemented on OpenFOAM. In this paper, based on codeStream function of original OpenFOAM, we design and implement curve boundary interface with reference to the interface of original OpenFOAM, so that users can use C++ code to describe curve boundary. Furthermore, in order to move the high-order points on the linear boundary to the curve boundary, we propose an algorithm to move each high-order point to a specific position on the curve, where the normal of this position passes through the origin point. Experimental results based on the flow around a cylinder show that curve boundary is needed by DGM numerical simulation, and DGM high-order simulation is much more efficient than DGM low-order. Typically, when the error of drag coefficient is about 0.03, the DGM high-order can save \(89.6\%\) time cost and \(83.0\%\) memory cost.

A High Order Discontinuous Galerkin Method Based RANS Turbulence Framework for OpenFOAM

Discontinuous Galerkin is one of the most promising high order method in CFD. However, there is a surprising lack of user-friendly software based on DGM. HopeFOAM is a high order extension of OpenFOAM. This paper designed a high order discontinuous Galerkin method based RANS turbulence framework on HopeFOAM, by inheriting the principle and user interfaces. The one equation turbulence model Spalart-Allmaras is integrated into the framework. User-friendly interfaces are provided to configure turbulence parameters and choosing calculation methods. The turbulence model and wall distance calculation are discretized by high order DGM. Results show that this framework can achieve similar simulation results comparing to literature.

An Adaptive Visualization Tool for High Order Discontinuous Galerkin Method with Quadratic Elements

High order discretization method is one of the most popular research topics on Computational Fluid Dynamics (CFD). However, the development of visualization tools suited for high order methods obtains not as much attention. Most of the software used to visualize numerical solutions do not support high order data format. To visualize the high order solution, the most common method is to tessellate the solution with linear subdivision and then generate the values by resampling. This paper describes an efficient approach for Discontinuous Galerkin Method (DGM) based on OpenFOAM and VTK. We design a method to estimate the visualization error and introduce gaussian quadrature method to calculate it. Under the limit of visualization error set by user, the high order DGM solution is tessellated into a set of quadratic elements and converted into VTK data. By implementing the interpolation interface, this tools can support other discretization methods. The tool is tested with a series of cases. Accurately visualization of geometric information and field attributes are obtained. Comparing to linear methods, less computation and space cost are needed to reach the same visualization error limit.

HACPar: An efficient parallel multiscale framework for hybrid atomistic–continuum simulation at the micro- and nanoscale

The hybrid atomistic–continuum coupling method based on domain decomposition serves as an important tool for the microfluidic simulation. However, major modifications to existing codes are often required to enable such simulations, which pose significant difficulties. In this article, in order to provide an efficient and easy-to-use software framework for field users, we propose a hybrid atomistic–continuum parallel coupling framework, named HACPar, based on open-source software platforms. We abstract the software architecture of the hybrid atomistic–continuum coupling framework based on geometric decomposition for the first time, demonstrate the detailed implementation of the framework, and present deep research on the coupling-oriented parallel issues which may improve the flexibility and efficiency of other multiscale parallel applications. The benchmark cases verify the correctness and efficiency of our HACPar framework. The benchmark results show that the scalability of the hybrid simulations is reached up to 1536 cores.