Relationship between the radial dynamics and the chemical production of a harmonically driven spherical bubble

The sonochemical activity and the radial dynamics of a harmonically excited spherical bubble are investigated numerically. A detailed model is employed capable to calculate the chemical production inside the bubble placed in water that is saturated with oxygen. Parameter studies are performed with the control parameters of the pressure amplitude, the forcing frequency and the bubble size. Three different definitions of collapse strengths (extracted from the radius vs. time curves) are examined and compared with the chemical output of various species. A mathematical formula is established to estimate the chemical output as a function of the collapse strength; thus, the chemical activity can be predicted without taking into account the chemical kinetics into the bubble model. The calculations are carried out by an in-house code exploiting the high processing power of professional graphics cards (GPUs).The results shown that chemical activity can be approximated qualitatively from the values of relative expansion. This could be helpful in order to optimise chemical output of sonochemical reactors either from measurement data or simulations as well.     

Real-time accurate Free-Form Deformation in terms of triangular Bezier surfaces

We implemented accurate FFD in terms of triangular Bezier surfaces as matrix multiplications in CUDA and rendered them via OpenGL. Experimental results show that the proposed algorithm is more efficient than the previous GPU acceleration algorithm and tessel- lation shader algorithms.     

Discontinuous Galerkin methods on graphics processing units for nonlinear hyperbolic conservation laws

We present a novel implementation of the modal DG method for hyperbolic conservation laws in two dimensions on graphics processing units (GPUs) using NVIDIA's Compute Unified Device Architecture. Both flexible and highly accurate, DG methods accommodate parallel architectures well as their discontinuous nature produces element‐local approximations. High‐performance scientific computing suits GPUs well, as these powerful, massively parallel, cost‐effective devices have recently included support for double‐precision floating‐point numbers. Computed examples for Euler equations over unstructured triangle meshes demonstrate the effectiveness of our implementation on an NVIDIA GTX 580 device. Profiling of our method reveals performance comparable with an existing nodal DG‐GPU implementation for linear problems. Copyright © 2014 John Wiley & Sons, Ltd.     

GPU‐accelerated direct numerical simulations of decaying compressible turbulence employing a GKM‐based solver

Gas Kinetic Method‐based flow solvers have become popular in recent years owing to their robustness in simulating high Mach number compressible flows. We evaluate the performance of the newly developed analytical gas kinetic method (AGKM) by Xuan et al. in performing direct numerical simulation of canonical compressible turbulent flow on graphical processing unit (GPU)s. We find that for a range of turbulent Mach numbers, AGKM results shows excellent agreement with high order accurate results obtained with traditional Navier–Stokes solvers in terms of key turbulence statistics. Further, AGKM is found to be more efficient as compared with the traditional gas kinetic method for GPU implementation. We present a brief overview of the optimizations performed on NVIDIA K20 GPU and show that GPU optimizations boost the speedup up‐to 40x as compared with single core CPU computations. Hence, AGKM can be used as an efficient method for performing fast and accurate direct numerical simulations of compressible turbulent flows on simple GPU‐based workstations. Copyright © 2016 John Wiley & Sons, Ltd.     

Fast and flexible gpu accelerated binding free energy calculations within the amber molecular dynamics package

Alchemical free energy (AFE) calculations based on molecular dynamics (MD) simulations are key tools in both improving our understanding of a wide variety of biological processes and accelerating the design and optimization of therapeutics for numerous diseases. Computing power and theory have, however, long been insufficient to enable AFE calculations to be routinely applied in early stage drug discovery. One of the major difficulties in performing AFE calculations is the length of time required for calculations to converge to an ensemble average. CPU implementations of MD‐based free energy algorithms can effectively only reach tens of nanoseconds per day for systems on the order of 50,000 atoms, even running on massively parallel supercomputers. Therefore, converged free energy calculations on large numbers of potential lead compounds are often untenable, preventing researchers from gaining crucial insight into molecular recognition, potential druggability and other crucial areas of interest. Graphics Processing Units (GPUs) can help address this. We present here a seamless GPU implementation, within the PMEMD module of the AMBER molecular dynamics package, of thermodynamic integration (TI) capable of reaching speeds of >140 ns/day for a 44,907‐atom system, with accuracy equivalent to the existing CPU implementation in AMBER. The implementation described here is currently part of the AMBER 18 beta code and will be an integral part of the upcoming version 18 release of AMBER. © 2018 Wiley Periodicals, Inc.     

Solid structures in a highly agitated bed of granular materials

A series of experiments are described in which bubbles and solid structures are produced in a highly agitated bed of vertically shaken granular materials. To identify the physical mechanisms behind bubbling, three-dimensional simulations of the aforementioned systems are performed on a graphics processing unit (GPU). The gas dynamics above and within shaken granular materials is solved using large-eddy simulations (LES) while the dynamics of grains is described through molecular dynamics. Here, the interaction between the grain surfaces is modeled using the generalized form of contact theory developed by Hertz. In addition, the coefficient of kinetic friction is assumed to depend on the relative velocity of slipping. The results show both a qualitative and a quantitative agreement between simulations and experiments. They imply that the instantaneous formation and failure of granular aggregates could play an important role in the nucleation, growth, departure and collapse of bubbles in shaken granular materials. This promising effort in GPU computing may position the GPU as a compelling future alternative to traditional simulation techniques.     

GPU引发的计算化学革命

综述了图形处理器(GPU)在计算化学中的应用和进展.首先简单介绍了GPU在科学计算中应用的发展,然后分别详细讲述了迄今几个使用GPU和CUDA(compute unified device architecture,显卡厂商Nvidia推出的计算平台)开发工具设计的量子化学计算和分子动力学(MD)模拟的算法和程序,尤其对目前唯一完全使用GPU技术开发的量子化学计算软件TeraChem做了完备的介绍,包括算法、实现的细节和程序目前的功能.此外,本文还对GPU在计算化学上将会发挥的作用做出了极为乐观的展望.     

Validation of EMMS-based drag model using lattice Boltzmann simulations on GPUs

Interphase momentum transport in heterogeneous gas–solid systems with multi-scale structure is of great importance in process engineering. In this article, lattice Boltzmann simulations are performed on graphics processing units (GPUs), the computational power of which exceeds that of CPUs by more than one order of magnitude, to investigate incompressible Newtonian flow in idealized multi-scale particle–fluid systems. The structure consists of a periodic array of clusters, each constructed by a bundle of cylinders. Fixed pressure boundary condition is implemented by applying a constant body force to the flow through the medium. The bounce-back scheme is adopted on the fluid–solid interfaces, which ensures the no-slip boundary condition. The structure is studied under a wide range of particle diameters and packing fractions, and the drag coefficient of the structure is found to be a function of voidages and fractions of the clusters, besides the traditional Reynolds number and the solid volume fractions. Parameters reflecting multi-scale characters are, therefore, demonstrated to be necessary in quantifying the drag force of heterogeneous gas–solid system. The numerical results in the range 0.1 ≤ Re ≤ 10 and 0 < ? < 0.25 are compared with Wen and Yu's correlation, Gibilaro equation, EMMS-based drag model, the Beetstra correlation and the Benyahia correlation, and good agreement is found between the simulations and the EMMS-based drag model for heterogeneous systems.     

GPU accelerated CESE method for 1D shock tube problems

In the present study, a GPU accelerated 1D space–time CESE method is developed and applied to shock tube problems with and without condensation. We have demonstrated how to implement the CESE algorithm to solve 1D shock tube problems using an older generation GPU (the NVIDIA 9800 GT) with relatively limited memory. To optimize the code performance, we used Shared Memory and solved the inter-Block boundary problem in two ways, namely the branch scheme and the overlapping scheme. The implementations of these schemes are discussed in detail and their performances are compared for the Sod shock tube problems. For the Sod problem without condensation, the speedup over an Intel CPU E7300 is 23 for the branch scheme and 41 for the overlapping scheme, respectively. While for problems with condensation, both schemes achieve higher acceleration ratios, 53 and 71, respectively. The higher speedup of the condensation case can be ascribed to the source term calculation which has a local dependence on the mesh point and the SOURCE kernel has a higher acceleration ratio.     

GPU-accelerated molecular dynamics simulation for study of liquid crystalline flows

We have developed a GPU-based molecular dynamics simulation for the study of flows of fluids with anisotropic molecules such as liquid crystals. An application of the simulation to the study of macroscopic flow (backflow) generation by molecular reorientation in a nematic liquid crystal under the application of an electric field is presented. The computations of intermolecular force and torque are parallelized on the GPU using the cell-list method, and an efficient algorithm to update the cell lists was proposed. Some important issues in the implementation of computations that involve a large number of arithmetic operations and data on the GPU that has limited high-speed memory resources are addressed extensively. Despite the relatively low GPU occupancy in the calculation of intermolecular force and torque, the computation on a recent GPU is about 50 times faster than that on a single core of a recent CPU, thus simulations involving a large number of molecules using a personal computer are possible. The GPU-based simulation should allow an extensive investigation of the molecular-level mechanisms underlying various macroscopic flow phenomena in fluids with anisotropic molecules.