In particle transport simulations, radiation effects are olden described by the discrete ordinates （Sn） form of Boltzmann equation. In each ordinate direction, the solution is computed by sweeping the radiation flux...In particle transport simulations, radiation effects are olden described by the discrete ordinates （Sn） form of Boltzmann equation. In each ordinate direction, the solution is computed by sweeping the radiation flux across the grid. Parallel Sn sweep on an unstructured grid can be explicitly modeled as topological traversal through an equivalent directed acyclic graph （DAG）, which is a data-driven algorithm. Its traditional design using MPI model results in irregular communication of massive short messages which cannot be efficiently handled by MPI runtime. Meanwhile, in high-end HPC cluster systems, multicore has become the standard processor configuration of a single node. The traditional data-driven algorithm of Sn sweeps has not exploited potential advantages of multi-threading of multicore on shared memory. These advantages, however, as we shall demonstrate, could provide an elegant solution resolving problems in the previous MPI-only design. In this paper, we give a new design of data-driven parallel Sn sweeps using hybrid MPI and Pthread programming, namely Sweep-H, to exploit hierarchical parallelism of processes and threads. With special multi-threading techniques and vertex schedule policy, Sweep-H gets more efficient communication and better load balance. We further present an analytical performance model for Sweep-H to reveal why and when it is advantageous over former MPI counterpart. On a 64-node multicore cluster system with 12 cores per node, 768 cores in total, Sweep-H achieves nearly linear scalability for moderate problem sizes, and better absolute performance than the previous times speedup on 64 nodes）. MPI algorithm on more than 16 nodes （by up to two展开更多
Hierarchical evolutionary algorithms based on genetic algorithms (GAs) and Nash strategy of game theory are proposed to accelerate the optimization process and implemented in transonic aerodynamic shape optimization p...Hierarchical evolutionary algorithms based on genetic algorithms (GAs) and Nash strategy of game theory are proposed to accelerate the optimization process and implemented in transonic aerodynamic shape optimization problems Inspired from the natural evolution history that different periods with certain environments have different criteria for the evaluations of individuals’ fitness, a hierarchical fidelity model is introduced to reach high optimization efficiency The shape of an NACA0012 based airfoil is optimized in maximizing the lift coefficient under a given transonic flow condition Optimized results are presented and compared with the single model results and traditional GA展开更多
Based on the first-order upwind and second-order central type of finite volume (UFV and CFV) scheme, upwind and central type of perturbation finite volume (UPFV and CPFV) schemes of the Navier-Stokes equations were de...Based on the first-order upwind and second-order central type of finite volume (UFV and CFV) scheme, upwind and central type of perturbation finite volume (UPFV and CPFV) schemes of the Navier-Stokes equations were developed. In PFV method, the mass fluxes of across the cell faces of the control volume (CV) were expanded into power series of the grid spacing and the coefficients of the power series were determined by means of the conservation equation itself. The UPFV and CPFV scheme respectively uses the same nodes and expressions as those of the normal first-order upwind and second-order central scheme, which is apt to programming. The results of numerical experiments about the flow in a lid-driven cavity and the problem of transport of a scalar quantity in a known velocity field show that compared to the first-order UFV and second-order CFV schemes, upwind PFV scheme is higher accuracy and resolution, especially better robustness. The numerical computation to flow in a lid-driven cavity shows that the under-relaxation factor can be arbitrarily selected ranging from (0.3) to (0.8) and convergence perform excellent with Reynolds number variation from 10~2 to 10~4.展开更多
基金supported by the National Natural Science Foundation of China under Grant Nos.60925009,61003062,61033009,61272134the National Basic 973 Program of China under Grant Nos.2011CB302502 and 2012CB316502
文摘In particle transport simulations, radiation effects are olden described by the discrete ordinates （Sn） form of Boltzmann equation. In each ordinate direction, the solution is computed by sweeping the radiation flux across the grid. Parallel Sn sweep on an unstructured grid can be explicitly modeled as topological traversal through an equivalent directed acyclic graph （DAG）, which is a data-driven algorithm. Its traditional design using MPI model results in irregular communication of massive short messages which cannot be efficiently handled by MPI runtime. Meanwhile, in high-end HPC cluster systems, multicore has become the standard processor configuration of a single node. The traditional data-driven algorithm of Sn sweeps has not exploited potential advantages of multi-threading of multicore on shared memory. These advantages, however, as we shall demonstrate, could provide an elegant solution resolving problems in the previous MPI-only design. In this paper, we give a new design of data-driven parallel Sn sweeps using hybrid MPI and Pthread programming, namely Sweep-H, to exploit hierarchical parallelism of processes and threads. With special multi-threading techniques and vertex schedule policy, Sweep-H gets more efficient communication and better load balance. We further present an analytical performance model for Sweep-H to reveal why and when it is advantageous over former MPI counterpart. On a 64-node multicore cluster system with 12 cores per node, 768 cores in total, Sweep-H achieves nearly linear scalability for moderate problem sizes, and better absolute performance than the previous times speedup on 64 nodes）. MPI algorithm on more than 16 nodes （by up to two
基金Start-up foundation item of the Educational Department of China for returnees
文摘Hierarchical evolutionary algorithms based on genetic algorithms (GAs) and Nash strategy of game theory are proposed to accelerate the optimization process and implemented in transonic aerodynamic shape optimization problems Inspired from the natural evolution history that different periods with certain environments have different criteria for the evaluations of individuals’ fitness, a hierarchical fidelity model is introduced to reach high optimization efficiency The shape of an NACA0012 based airfoil is optimized in maximizing the lift coefficient under a given transonic flow condition Optimized results are presented and compared with the single model results and traditional GA
文摘Based on the first-order upwind and second-order central type of finite volume (UFV and CFV) scheme, upwind and central type of perturbation finite volume (UPFV and CPFV) schemes of the Navier-Stokes equations were developed. In PFV method, the mass fluxes of across the cell faces of the control volume (CV) were expanded into power series of the grid spacing and the coefficients of the power series were determined by means of the conservation equation itself. The UPFV and CPFV scheme respectively uses the same nodes and expressions as those of the normal first-order upwind and second-order central scheme, which is apt to programming. The results of numerical experiments about the flow in a lid-driven cavity and the problem of transport of a scalar quantity in a known velocity field show that compared to the first-order UFV and second-order CFV schemes, upwind PFV scheme is higher accuracy and resolution, especially better robustness. The numerical computation to flow in a lid-driven cavity shows that the under-relaxation factor can be arbitrarily selected ranging from (0.3) to (0.8) and convergence perform excellent with Reynolds number variation from 10~2 to 10~4.
