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The paper presents a numerical solution to the heat wave motion problem for a degenerate second-order nonlinear parabolic equation with a source term. The nonlinearity is conditioned by the power dependence of the heat conduction coefficient on temperature. The problem for the case of two spatial variables is considered with the boundary condition specifying the heat wave motion law. A new solution algorithm based on an expansion in radial basis functions and the boundary element method is proposed. The solution is constructed stepwise in time with finite difference time approximation. At each time step, a boundary value problem for the Poisson equation corresponding to the original equation at a fixed time is solved. The solution to this problem is constructed iteratively as the sum of a particular solution to the nonhomogeneous equation and a solution to the corresponding homogeneous equation satisfying the boundary conditions. The homogeneous equation is solved by the boundary element method. The particular solution is sought by the collocation method using inhomogeneity expansion in radial basis functions. The calculation algorithm is optimized by parallelizing the computations. The algorithm is implemented as a program written in the C++ language. The parallel computations are organized by using the OpenCL standard, and this allows one to run the same parallel code either on multi-core CPUs or on graphic CPUs. Test cases are solved to evaluate the effectiveness of the proposed solution method and the correctness of the developed computational technique. The calculation results are compared with known exact solutions, as well as with the results we obtained earlier. The accuracy of the solutions and the calculation time are estimated. The effectiveness of using various systems of radial basis functions to solve the problems under study is analyzed. The most suitable system of functions is selected. The implemented complex computational experiment shows higher calculation accuracy of the proposed new algorithm than that of the previously developed one.

The work is devoted to numerical modeling of two-phase flows, namely, the calculation of supersonic flow around a blunt body by a viscous gas flow with an admixture of large high inertia particles. The system of unsteady Navier – Stokes equations is numerically solved by the meshless method. It uses the cloud of points in space to represent the fields of gas parameters. The spatial derivatives of gas parameters and functions are approximated by the least square method to calculate convective and viscous fluxes in the Navier – Stokes system of equations. The convective fluxes are calculated by the HLLC method. The third-order MUSCL reconstruction scheme is used to achieve high order accuracy. The viscous fluxes are calculated by the second order approximation scheme. The streamlined body surface is represented by a model of an isothermal wall. It implements the conditions for the zero velocity and zero pressure gradient, which is also modeled using the least squares method.

Every moving body is surrounded by its own cloud of points belongs to body’s domain and moving along with it in space. The explicit three-sage Runge–Kutta method is used to solve numerically the system of gas dynamics equations in the main coordinate system and local coordinate systems of each particle.

Two methods for the moving objects modeling with reverse impact on the gas flow have been implemented. The first one uses stationary point clouds with fixed neighbors within the same domain. When regions overlap, some nodes of one domain, for example, the boundary nodes of the particle domain, are excluded from the calculation and filled with the values of gas parameters from the nearest nodes of another domain using the least squares approximation of gradients. The internal nodes of the particle domain are used to reconstruct the gas parameters in the overlapped nodes of the main domain. The second method also uses the exclusion of nodes in overlapping areas, but in this case the nodes of another domain take the place of the excluded neighbors to build a single connected cloud of nodes. At the same time, some of the nodes are moving, and some are stationary. Nodes membership to different domains and their relative speed are taken into account when calculating fluxes.

The results of modeling the motion of a particle in a stationary gas and the flow around a stationary particle by an incoming flow at the same relative velocity show good agreement for both presented methods.

The aim of research is to develop software system for solving gas dynamic problem in multiply connected integration domains of regular shape by high-performance computing system. Comparison of the various technologies of parallel computing has been done. The program complex is implemented using multithreaded parallel systems to organize both multi-core and massively parallel calculation. The comparison of numerical results with known model problems solutions has been done. Research of performance of different computing platforms has been done.

In this article the experience of reading “CUDA and OpenCL programming” course during high perfomance computing summer school MIPT-2010 is analyzed. Content of lectures and practical tasks, as well as manner of presenting of the material are regarded. Performance issues of different algorithms implemented by students at practical training session are dicussed.

A hybrid cluster implies the use of computational devices with radically different architectures. Usually, these are conventional CPU architecture (e.g. x86_64) and GPU architecture (e. g. NVIDIA CUDA). Creating and exploiting such a cluster requires some experience: in order to harness all computational power of the described system and get substantial speedup for computational tasks many factors should be taken into account. These factors consist of hardware characteristics (e.g. network infrastructure, a type of data storage, GPU architecture) as well as software stack (e.g. MPI implementation, GPGPU libraries). So, in order to run scientific applications GPU capabilities, software features, task size and other factors should be considered.

This report discusses opportunities and problems of hybrid computations. Some statistics from tests programs and applications runs will be demonstrated. The main focus of interest is open source applications (e. g. OpenFOAM) that support GPGPU (with some parts rewritten to use GPGPU directly or by replacing libraries).

There are several approaches to organize heterogeneous computations for different GPU architectures out of which CUDA library and OpenCL framework are compared. CUDA library is becoming quite typical for hybrid systems with NVIDIA cards, but OpenCL offers portability opportunities which can be a determinant factor when choosing framework for development. We also put emphasis on multi-GPU systems that are often used to build hybrid clusters. Calculations were performed on a hybrid cluster of SPbU computing center.

Modeling of carbon nanostructures by means of classical molecular dynamics requires a lot of computations. One of the ways to improve the performance of basic algorithms is to transform them for running on SIMD-type computing systems such as systems with dedicated GPU. In this work we describe the development of algorithms for computation of many-body interaction based on Tersoff and embedded-atom potentials by means of OpenCL technology. OpenCL standard provides universality and portability of the algorithms and can be successfully used for development of the software for heterogeneous computing systems. The performance of algorithms is evaluated on CPU and GPU hardware platforms. It is shown that concurrent memory writes is effective for Tersoff bond order potential. The same approach for embedded-atom potential is shown to be slower than algorithm without concurrent memory access. Performance evaluation shows a significant GPU acceleration of energy-force evaluation algorithms for many-body potentials in comparison to the corresponding serial implementations.