Acceleration of Turbomachinery Steady Simulations on GPU
نویسندگان
چکیده
Steady state simulations in Computational Fluid Dynamics (CFD), which rely on implicit time integration, are not experiencing great accelerations on GPUs. Moreover, most of the reported acceleration effort concerns solving the linear system of equations while neglecting the acceleration potential of running the entire simulation on the GPU. In this paper, we present the software implementation of an implicit RANS CFD solver, which is fully running on GPU. We use the GMRES linear solver of the Paralution package combined with the incomplete LU factorization for the preconditioning. We propose also a control mechanism on-demand factorization capable of reducing the number of times an incomplete LU factorization is performed. The on-demand factorization accelerates the linear solver without altering the flow convergence. The GPU implementation achieved a speedups of 9.2x compared to a singlecore CPU and 3.5x compared to a 4-cores CPU for 3-D flow predictions in turbine applications.
منابع مشابه
A GPU-accelerated Navier-Stokes Solver for Steady Turbomachinery Simulations
Any tiny improvement of modern turbomachinery components require nowadays a large amount of design evaluations. Every evaluation runs time consuming simulations. Reducing the computational cost of the simulations allows to run more evaluations, thus reaching a higher design improvement. In this work, an Nvidia Graphics Processing Unit (GPU) of Kepler generation is used to accelerate the FiniteV...
متن کاملMulti-GPU acceleration of direct pore-scale modeling of fluid flow in natural porous media
Modified Moving Particle Semi-implicit (MMPS) is a particle-based method used to simulate pore-scale fluid flow through disordered porous media. We present a multi-GPU implementation of MMPS for hybrid CPU–GPU clusters using NVIDIA’s Compute Unified Device Architecture (CUDA). Message Passing Interface (MPI) functions are used to communicate between different nodes of the cluster and hence thei...
متن کاملGPU acceleration of Eulerian–Lagrangian particle-laden turbulent flow simulations
Acceleration of an existing MPI-based, particle-laden turbulent flow simulation code is achieved using up to four NVIDIA GPU devices. The overall design is to transfer the entire flow velocity, temperature, and humidity fields to each device, and compute particle trajectories entirely on the GPU hardware. For one-way coupled turbulent flow simulations, accurate simulations can be achieved for l...
متن کاملComputation of Unsteady Nonlinear Flows in Cascades Using a Harmonic Balance Technique
A harmonic balance technique for modeling unsteady nonlinear ows in turbomachinery is presented. The analysis exploits the fact that many unsteady ows of interest in turbomachinery are periodic in time. Thus, the unsteady ow conservation variables may be represented by a Fourier series in time with spatially varying coef cients. This assumption leads to a harmonic balance form of the Eul...
متن کاملImplementation of the direction of arrival estimation algorithms by means of GPU-parallel processing in the Kuda environment (Research Article)
Direction-of-arrival (DOA) estimation of audio signals is critical in different areas, including electronic war, sonar, etc. The beamforming methods like Minimum Variance Distortionless Response (MVDR), Delay-and-Sum (DAS), and subspace-based Multiple Signal Classification (MUSIC) are the most known DOA estimation techniques. The mentioned methods have high computational complexity. Hence using...
متن کامل