Performance of a projection method for incompressible flows on heterogeneous hardware. (22nd October 2015)

• Record Type: Journal Article
• Authors: Kempe, Tobias; Aguilera, Alvaro; Nagel, Wolfgang; Fröhlich, Jochen
• Is Part Of: Computers & fluids. Volume 121(2015)
• Page Start: 37
• Page End: 43
• Publication Date: 2015-10-22
• Subjects: Incompressible flow -- Projection method -- Poisson equation -- GPU acceleration -- PETSc -- Hypre; Fluid dynamics -- Data processing -- Periodicals; 532.050285
• DOI: 10.1016/j.compfluid.2015.07.028
• Languages: English
• ISSNs: 0045-7930

Abstract

Highlights: Performance of a projection method on CPU and GPU is investigated. Linear solvers of libraries PETSc and hypre compared systematically. GPU acceleration using built-in GPU solvers of PETSc. Power consumption is measured to assess energy efficiency. Abstract: Practical experiments on the flow in a lid-driven cavity are carried out to compare the performance of a second-order finite volume Navier–Stokes solver for incompressible fluids employing a projection method, when using various linear solver libraries on central processing units (CPUs) and graphical processing units (GPUs). The goal of the paper is to identify the potential of GPU acceleration using the built-in GPU solvers of PETSc and to provide information if the usage of GPUs is beneficial for this type of fluid solver in terms of performance and implementation effort. Additionally, energy consumption having emerged as another important goal of optimization in high-performance computing is addressed as well. In this study, the solvers available in the PETSc library, which are running on CPU as well as with GPU support, are compared with the solvers provided by the hypre library in a systematic way. The power consumption of the CPU and the GPU during the solution is measured to assess the energy efficiency in terms of the performance-per-Watt ratio. It is found that for the considered numerical scheme the usage of iterative solvers on current GPU systems is not necessarily beneficial, neither in terms of performance nor in terms of energy consumption, since both libraries, PETSc and hypre, provide highly-optimized solvers for massively parallel CPU systems.