2026-08-16T12:01:07Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:7604 2024-03-12T11:58:38Z ddc:004 open_access

Graph Partitioning with Acyclicity Constraints Moreira, Orlando Popp, Merten Schulz, Christian Graph Partitioning Computer Vision and Imaging Applications Graphs are widely used to model execution dependencies in applications. In particular, the NP-complete problem of partitioning a graph under constraints receives enormous attention by researchers because of its applicability in multiprocessor scheduling. We identified the additional constraint of acyclic dependencies between blocks when mapping streaming applications to a heterogeneous embedded multiprocessor. Existing algorithms and heuristics do not address this requirement and deliver results that are not applicable for our use-case. In this work, we show that this more constrained version of the graph partitioning problem is NP-complete and present heuristics that achieve a close approximation of the optimal solution found by an exhaustive search for small problem instances and much better scalability for larger instances. In addition, we can show a positive impact on the schedule of a real imaging application that improves communication volume and execution time. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Orlando Moreira and Merten Popp and Christian Schulz 2017 Is Part Of LIPIcs, Volume 75, 16th International Symposium on Experimental Algorithms (SEA 2017) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.SEA.2017.30 urn:nbn:de:0030-drops-76042 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2017.30 eng https://creativecommons.org/licenses/by/3.0/legalcode