https://puma.ub.uni-stuttgart.de/user/ipvs-sgs/parallel_computingPUMA RSS feed for /user/ipvs-sgs/parallel_computing2026-04-23T07:26:53+02:00https://puma.ub.uni-stuttgart.de/bibtex/224e2efdd8274989c057475778965fb3b/ipvs-sgsipvs-sgs2020-07-27T15:19:28+02:00semi-Lagrangian fast_multipole parallel_computing adaptive_mesh_refinement from:ajaust <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Arash Bakhtiari" itemprop="url" href="/person/1ecb2ea5adabcad86c40cc4c53e4d7cfc/author/0"><span itemprop="name">A. Bakhtiari</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Dhairya Malhotra" itemprop="url" href="/person/1ecb2ea5adabcad86c40cc4c53e4d7cfc/author/1"><span itemprop="name">D. Malhotra</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Amir Raoofy" itemprop="url" href="/person/1ecb2ea5adabcad86c40cc4c53e4d7cfc/author/2"><span itemprop="name">A. Raoofy</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Miriam Mehl" itemprop="url" href="/person/1ecb2ea5adabcad86c40cc4c53e4d7cfc/author/3"><span itemprop="name">M. Mehl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hans-Joachim Bungartz" itemprop="url" href="/person/1ecb2ea5adabcad86c40cc4c53e4d7cfc/author/4"><span itemprop="name">H. Bungartz</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="George Biros" itemprop="url" href="/person/1ecb2ea5adabcad86c40cc4c53e4d7cfc/author/5"><span itemprop="name">G. Biros</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis</span>, </em></span><em>Seite <span itemprop="pagination">1--12</span>. </em><em>Piscataway, NJ, USA, </em><em><span itemprop="publisher">IEEE Press</span>, </em>(<em><span>November 2016<meta content="November 2016" itemprop="datePublished"/></span></em>)</span>Mon Jul 27 15:19:28 CEST 2020Piscataway, NJ, USAProceedings of the International Conference for High Performance Computing, Networking, Storage and AnalysisNovember1--12{A Parallel Arbitrary-order Accurate AMR Algorithm for the Scalar Advection-diffusion Equation}Konferenz-Beitrag2016semi-Lagrangian fast_multipole parallel_computing adaptive_mesh_refinement from:ajaust We present a numerical method for solving the scalar advection-diffusion equation using adaptive mesh re- finement. Our solver has three unique characteristics: (1) it supports arbitrary-order accuracy in space; (2) it allows different discretizations for the velocity and scalar advected quantity; and (3) it combines the method of characteristics with an integral equation formulation. In particular, our solver is based on a second-order accurate, unconditionally stable, semi-Lagrangian scheme combined with a spatially-adaptive Chebyshev octree for discretization. We study the convergence, single-node perfor- mance, strong scaling, and weak scaling of our scheme for several challenging flows that cannot be resolved efficiently without using high-order accurate discretizations. For example, we consider problems for which switching from 4th order to 14th order approximation results in two orders of magnitude speedups for a fixed accuracy. For our largest run, we solve a problem with one billion unknowns on a tree with maximum depth equal to 10 and 14th-order elements on 16,384 cores on the {\^a}€STAMPEDE{\^a}€ system at the Texas Advanced Computing Center.