An Optimizing Code Generator for a Class of Lattice-Boltzmann Computations

The Lattice-Boltzmann method (LBM), a promising new particle-based simulation technique for complex and multiscale fluid flows, has seen tremendous adoption in recent years in computational fluid dynamics. Even with a state-of-the-art LBM solver such as Palabos, a user has to still manually write the program using library-supplied primitives. We propose an automated code generator for a class of LBM computations with the objective to achieve high performance on modern architectures. Few studies have looked at time tiling for LBM codes. We exploit a key similarity between stencils and LBM to enable polyhedral optimizations and in turn time tiling for LBM. We also characterize the performance of LBM with the Roofline performance model. Experimental results for standard LBM simulations like Lid Driven Cavity, Flow Past Cylinder, and Poiseuille Flow show that our scheme consistently outperforms Palabos-on average by up to 3x while running on 16 cores of an Intel Xeon (Sandybridge). We also obtain an improvement of 2.47x on the SPEC LBM benchmark.

A dynamic coupling model for hybrid atomistic-continuum computations

A dynamic coupling model is developed for a hybrid atomistic-continuum computation in micro- and nano-fluidics. In the hybrid atomistic-continuum computation, a molecular dynamics (MD) simulation is utilized in one region where the continuum assumption breaks down and the Navier-Stokes (NS) equations are used in another region where the continuum assumption holds. In the overlapping part of these two regions, a constrained particle dynamics is needed to couple the MD simulation and the NS equations. The currently existing coupling models for the constrained particle dynamics have a coupling parameter, which has to be empirically determined. In the present work, a novel dynamic coupling model is introduced where the coupling parameter can be calculated as the computation progresses rather than inputing a priori. The dynamic coupling model is based on the momentum constraint and exhibits a correct relaxation rate. The results from the hybrid simulation on the Couette flow and the Stokes flow are in good agreement with the data from the full MD simulation and the solutions of the NS equations, respectively. (c) 2007 Elsevier Ltd. All rights reserved.

Multiscale Method for Turbulent-Flow Computations

A main method of predicting turbulent flows is to solve LES equations, which was called traditional LES method. The traditional LES method solves the motions of large eddies of size larger than filtering scale An while modeling unresolved scales less than Delta_n. Hughes et al argued that many shortcomings of the traditional LES approaches were associated with their inabilities to successfully differentiate between large and small scales. One may guess that a priori scale-separation would be better, because it can predict scale-interaction well compared with posteriori scale-separation. To this end, a multi-scale method was suggested to perform scale-separation computation. The primary contents of the multiscale method are l) A space average is used to differentiate scale. 2) The basic equations include the large scale equations and fluctuation equations. 3) The large-scale equations and fluctuation equations are coupled through turbulent stress terms. We use the multiscale equations of n=2, i.e., the large and small scale (LSS) equations, to simulate 3-D evolutions of a channel flow and a planar mixing layer flow Some interesting results are given.