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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/224e2efdd8274989c057475778965fb3b/ipvs-sgs",         
         "tags" : [
            "semi-Lagrangian","fast_multipole","parallel_computing","adaptive_mesh_refinement","from:ajaust"
         ],
         
         "intraHash" : "24e2efdd8274989c057475778965fb3b",
         "interHash" : "ecb2ea5adabcad86c40cc4c53e4d7cfc",
         "label" : "A Parallel Arbitrary-order Accurate AMR Algorithm for the Scalar Advection-diffusion Equation",
         "user" : "ipvs-sgs",
         "description" : "",
         "date" : "2020-07-27 15:19:28",
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         "pub-type": "inproceedings",
         "booktitle": "Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis","publisher":"IEEE Press","address":"Piscataway, NJ, USA",
         "year": "2016", 
         "url": "http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-43&engl=0", 
         
         "author": [ 
            "Arash Bakhtiari","Dhairya Malhotra","Amir Raoofy","Miriam Mehl","Hans-Joachim Bungartz","George Biros"
         ],
         "authors": [
         	
            	{"first" : "Arash",	"last" : "Bakhtiari"},
            	{"first" : "Dhairya",	"last" : "Malhotra"},
            	{"first" : "Amir",	"last" : "Raoofy"},
            	{"first" : "Miriam",	"last" : "Mehl"},
            	{"first" : "Hans-Joachim",	"last" : "Bungartz"},
            	{"first" : "George",	"last" : "Biros"}
         ],
         "pages": "1--12","abstract": "We present a numerical method for solving the scalar advection-diffusion\n      equation using adaptive mesh re- finement. Our solver has three unique\n      characteristics: (1) it supports arbitrary-order accuracy in space; (2) it\n      allows different discretizations for the velocity and scalar advected quantity;\n      and (3) it combines the method of characteristics with an integral equation\n      formulation. In particular, our solver is based on a second-order accurate,\n      unconditionally stable, semi-Lagrangian scheme combined with a\n      spatially-adaptive Chebyshev octree for discretization. We study the\n      convergence, single-node perfor- mance, strong scaling, and weak scaling of our\n      scheme for several challenging flows that cannot be resolved efficiently\n      without using high-order accurate discretizations. For example, we consider\n      problems for which switching from 4th order to 14th order approximation results\n      in two orders of magnitude speedups for a fixed accuracy. For our largest run,\n      we solve a problem with one billion unknowns on a tree with maximum depth equal\n      to 10 and 14th-order elements on 16,384 cores on the â\u20AC\u009DSTAMPEDEâ\u20AC\u009D system at\n      the Texas Advanced Computing Center.",
         "ee" : "http://dl.acm.org/citation.cfm?id=3014904.3014963",
         
         "isbn" : "978-1-4673-8815-3",
         
         "language" : "Englisch",
         
         "cr-category" : "J.0 Computer Applications General",
         
         "department" : "Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Simulation großer Systeme",
         
         "bibtexKey": "bakhtiari2016parallel"

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