Parallelisation to Several Tens-of-Thousands of Cores

In this Section a detailed and quantitative understanding is provided of how algorithms should be designed and implemented to effectively target a range of existing and emerging ‘massively parallel’ hardware platforms. The goal set up in the TILDA project was to demonstrate the capability and efficiency of the high-order methods developed by the partners on up to 50,000 cores.

[1]  Eric Petit,et al.  Divide and Conquer Parallelization of Finite Element Method Assembly , 2013, PARCO.

[2]  Freddie D. Witherden,et al.  Heterogeneous Computing on Mixed Unstructured Grids with PyFR , 2014, ArXiv.

[3]  Jens Jägersküpper,et al.  DLR-Project Digital-X: Next generation CFD solver 'Flucs' , 2016 .

[4]  Thomas D. Economon,et al.  Stanford University Unstructured (SU 2 ): An open-source integrated computational environment for multi-physics simulation and design , 2013 .

[5]  Christophe Geuzaine,et al.  Gmsh: A 3‐D finite element mesh generator with built‐in pre‐ and post‐processing facilities , 2009 .

[6]  Paul G. Tucker,et al.  Computation of unsteady turbomachinery flows: Part 1Progress and challenges , 2011 .

[7]  Rajeev Thakur,et al.  Enabling communication concurrency through flexible MPI endpoints , 2014, Int. J. High Perform. Comput. Appl..

[8]  Howard P. Hodson,et al.  Development of Blade Profiles for Low-Pressure Turbine Applications , 1997 .

[9]  Frederic Chalot,et al.  Higher-Order RANS and DES in an Industrial Stabilized Finite Element Code , 2015 .

[10]  Leonhard Fottner,et al.  Experimental and Numerical Investigation of Wake-Induced Transition on a Highly Loaded LP Turbine at Low Reynolds Numbers , 2000 .

[11]  P. Tesini,et al.  On the flexibility of agglomeration based physical space discontinuous Galerkin discretizations , 2012, J. Comput. Phys..

[12]  Víctor López,et al.  MPI+X: task-based parallelisation and dynamic load balance of finite element assembly , 2018, International Journal of Computational Fluid Dynamics.

[13]  Freddie D. Witherden,et al.  PyFR: An open source framework for solving advection-diffusion type problems on streaming architectures using the flux reconstruction approach , 2013, Comput. Phys. Commun..

[14]  V. N. Rao,et al.  Numerical Investigation of Contrasting Flow Physics in Different Zones of a High-Lift Low Pressure Turbine Blade , 2015 .

[15]  John H. Kolias,et al.  A CONSERVATIVE STAGGERED-GRID CHEBYSHEV MULTIDOMAIN METHOD FOR COMPRESSIBLE FLOWS , 1995 .

[16]  W. H. Reed,et al.  Triangular mesh methods for the neutron transport equation , 1973 .

[17]  M. de la Llave Plata,et al.  Aghora: A High-Order DG Solver for Turbulent Flow Simulations , 2015 .

[18]  Vipin Kumar,et al.  A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs , 1998, SIAM J. Sci. Comput..

[19]  Norbert Kroll,et al.  ADIGMA: A European Project on the Development of Adaptive Higher Order Variational Methods for Aerospace Applications , 2010 .

[20]  Leonhard Fottner,et al.  A Test Case for the Numerical Investigation of Wake Passing Effects on a Highly Loaded LP Turbine Cascade Blade , 2001 .

[21]  Lorenzo Botti,et al.  Influence of Reference-to-Physical Frame Mappings on Approximation Properties of Discontinuous Piecewise Polynomial Spaces , 2012, J. Sci. Comput..

[22]  T. Hughes,et al.  A new finite element formulation for computational fluid dynamics. X - The compressible Euler and Navier-Stokes equations , 1991 .

[23]  Vincent Couaillier,et al.  Turbulent jet simulation using high-order DG methods for aeroacoustics analysis , 2017, 1705.08723.

[24]  Freddie D. Witherden,et al.  On the utility of GPU accelerated high-order methods for unsteady flow simulations: A comparison with industry-standard tools , 2017, J. Comput. Phys..

[25]  Q. V. Dinh,et al.  A Multi-platform Shared- or Distributed-Memory Navier-Stokes Code , 1997, Parallel CFD.

[26]  Antony Jameson,et al.  A New Class of High-Order Energy Stable Flux Reconstruction Schemes , 2011, J. Sci. Comput..

[27]  H. T. Huynh,et al.  A Flux Reconstruction Approach to High-Order Schemes Including Discontinuous Galerkin Methods , 2007 .

[28]  Rémi Abgrall,et al.  On essentially non-oscillatory schemes on unstructured meshes: analysis and implementation , 1994 .

[29]  S. Osher,et al.  Uniformly high order accurate essentially non-oscillatory schemes, 111 , 1987 .

[30]  Chi-Wang Shu,et al.  Runge–Kutta Discontinuous Galerkin Methods for Convection-Dominated Problems , 2001, J. Sci. Comput..

[31]  Zdeněk Johan,et al.  Data parallel finite element techniques for large-scale computational fluid dynamics , 1992 .

[32]  P. Frederickson,et al.  Higher order solution of the Euler equations on unstructured grids using quadratic reconstruction , 1990 .

[33]  J. Hesthaven,et al.  Nodal Discontinuous Galerkin Methods: Algorithms, Analysis, and Applications , 2007 .

[34]  R. Lewis,et al.  Low-storage, Explicit Runge-Kutta Schemes for the Compressible Navier-Stokes Equations , 2000 .

[35]  T. Hughes,et al.  A multi-element group preconditioned GMRES algorithm for nonsymmetric systems arising in finite element analysis , 1989 .

[36]  Marcel Vinokur,et al.  Spectral difference method for unstructured grids I: Basic formulation , 2006, J. Comput. Phys..

[37]  Hans-Peter Kersken,et al.  HICFD: Highly Efficient Implementation of CFD Codes for HPC Many-Core Architectures , 2010, CHPC.

[38]  S. Osher,et al.  Weighted essentially non-oscillatory schemes , 1994 .

[39]  Jens Jägersküpper,et al.  GASPI - A Partitioned Global Address Space Programming Interface , 2012, Facing the Multicore-Challenge.

[40]  Jochen Gier,et al.  Designing Low Pressure Turbines for Optimized Airfoil Lift , 2010 .

[41]  Nan Wu,et al.  On the GPU performance of cell-centered finite volume method over unstructured tetrahedral meshes , 2013, IA3 '13.

[42]  William Gropp,et al.  CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences , 2014 .

[43]  Z. Wang High-order methods for the Euler and Navier–Stokes equations on unstructured grids , 2007 .