{"year":"2010","status":"public","author":[{"full_name":"Gehweiler, Joachim","last_name":"Gehweiler","first_name":"Joachim"},{"first_name":"Henning","full_name":"Meyerhenke, Henning","last_name":"Meyerhenke"}],"abstract":[{"lang":"eng","text":"Load balancing is an important requirement for the efficient execu-tion of parallel numerical simulations. In particular when the simulation domainchanges over time, the mapping of computational tasks to processors needs tobe  modified  accordingly.  State-of-the-art  libraries  for  this  problem  are  basedon graph repartitioning. They have a number of drawbacks, including the opti-mized metric and the difficulty of parallelizing the popular repartitioning heuris-tic Kernighan-Lin (KL).Here we further explore the very promising diffusion-based graph partitioningalgorithm DIBAP (Meyerhenke et al., JPDC 69(9):750–761, 2009) by adaptingDIBAP  to  the  related  problem  of  load  balancing.  Experiments  with  graph  se-quences that imitate adaptive numerical simulations demonstrate the applicabilityand high quality of DIBAP for load balancing by repartitioning. Compared to thefaster state-of-the-art repartitioners PARMETIS and parallel JOSTLE, DIBAP’ssolutions have partitions with significantly fewer external edges and boundarynodes  and  the  resulting  average  migration  volume  in  the  important  maximumnorm is also the best in most cases.We also prove that one of DIBAP’s key components optimizes a relaxed versionof the minimum edge cut problem. Moreover, we hint at a distributed algorithmbased on ideas used in DIBAP for clustering a virtual P2P supercomputer."}],"department":[{"_id":"63"}],"_id":"19016","title":"On Dynamic Graph Partitioning and Graph Clustering using Diffusion","date_created":"2020-09-04T10:45:47Z","related_material":{"link":[{"url":"https://drops.dagstuhl.de/opus/volltexte/2010/2798/pdf/10261.MeyerhenkeHenning.Paper.2798.pdf","relation":"confirmation"}]},"citation":{"ieee":"J. Gehweiler and H. Meyerhenke, “On Dynamic Graph Partitioning and Graph Clustering using Diffusion,” in <i>Dagstuhl Seminar Proceedings 10261: Algorithm Engineering</i>, 2010.","mla":"Gehweiler, Joachim, and Henning Meyerhenke. “On Dynamic Graph Partitioning and Graph Clustering Using Diffusion.” <i>Dagstuhl Seminar Proceedings 10261: Algorithm Engineering</i>, 2010.","ama":"Gehweiler J, Meyerhenke H. On Dynamic Graph Partitioning and Graph Clustering using Diffusion. In: <i>Dagstuhl Seminar Proceedings 10261: Algorithm Engineering</i>. ; 2010.","bibtex":"@inproceedings{Gehweiler_Meyerhenke_2010, title={On Dynamic Graph Partitioning and Graph Clustering using Diffusion}, booktitle={Dagstuhl Seminar Proceedings 10261: Algorithm Engineering}, author={Gehweiler, Joachim and Meyerhenke, Henning}, year={2010} }","apa":"Gehweiler, J., &#38; Meyerhenke, H. (2010). On Dynamic Graph Partitioning and Graph Clustering using Diffusion. In <i>Dagstuhl Seminar Proceedings 10261: Algorithm Engineering</i>.","short":"J. Gehweiler, H. Meyerhenke, in: Dagstuhl Seminar Proceedings 10261: Algorithm Engineering, 2010.","chicago":"Gehweiler, Joachim, and Henning Meyerhenke. “On Dynamic Graph Partitioning and Graph Clustering Using Diffusion.” In <i>Dagstuhl Seminar Proceedings 10261: Algorithm Engineering</i>, 2010."},"user_id":"15415","language":[{"iso":"eng"}],"publication":"Dagstuhl Seminar Proceedings 10261: Algorithm Engineering","type":"conference","date_updated":"2022-01-06T06:53:57Z"}