Scotch

Scotch 3.1 User’s Guide. The efficient execution of a parallel program on a parallel machine requires good placement of the communicating processes of the program onto the processors of the machine. When both the program and the machine are modeled in terms of weighted unoriented graphs, this problem amounts to static graph mapping. This document describes the capabilities and operations of Scotch, a software package devoted to graph mapping, based on the Dual Recursive Bipartitioning algorithm. Predefined mapping strategies allow for recursive application of any of several graph bipartitioning methods, including Fiduccia-Mattheyses, Gibbs-Poole-Stockmeyer, and multi-level methods. Scotch can map any weighted process graph onto any weighted target graph, whether they are connected or not. We give brief descriptions of the algorithm and bipartitioning methods, detail the input/output formats, instructions for use, and installation procedures, and provide a number of examples.


References in zbMATH (referenced in 82 articles )

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  1. Al Daas, Hussam; Jolivet, Pierre; Scott, Jennifer A.: A robust algebraic domain decomposition preconditioner for sparse normal equations (2022)
  2. Margetis, A.-S. I.; Papoutsis-Kiachagias, E. M.; Giannakoglou, K. C.: Lossy compression techniques supporting unsteady adjoint on 2D/3D unstructured grids (2021)
  3. Thune, Andreas; Cai, Xing; Rustad, Alf Birger: On the impact of heterogeneity-aware mesh partitioning and non-contributing computation removal on parallel reservoir simulations (2021)
  4. Ye, Shuai; Xu, Xinhai; An, Hengbin; Yang, Xuejun: A supplementary strategy for coarsening in algebraic multigrid (2021)
  5. Davis, Timothy A.; Hager, William W.; Kolodziej, Scott P.; Yeralan, S. Nuri: Algorithm 1003: Mongoose, a graph coarsening and partitioning library (2020)
  6. Klockiewicz, Bazyli; Darve, Eric: Sparse hierarchical preconditioners using piecewise smooth approximations of eigenvectors (2020)
  7. Li, Qi; Zhong, Jiang; Cao, Zehong; Li, Xue: Optimizing streaming graph partitioning via a heuristic greedy method and caching strategy (2020)
  8. Selvitopi, Oguz; Acer, Seher; Manguoğlu, Murat; Aykanat, Cevdet: The effect of various sparsity structures on parallelism and algorithms to reveal those structures (2020)
  9. Du, Cheng-Han; Chiou, Yih-Peng; Wang, Weichung: Compressed hierarchical Schur algorithm for frequency-domain analysis of photonic structures (2019)
  10. Herrmann, Julien; Özkaya, M. Yusuf; Uçar, Bora; Kaya, Kamer; Çatalyürek, ÜMit V.: Multilevel algorithms for acyclic partitioning of directed acyclic graphs (2019)
  11. Hoang, Thi-Thao-Phuong; Leng, Wei; Ju, Lili; Wang, Zhu; Pieper, Konstantin: Conservative explicit local time-stepping schemes for the shallow water equations (2019)
  12. Agreste, Santa; Ricciardello, Angela: An overlapping domain decomposition method for large-scale problems (2018)
  13. Creech, Angus C. W.; Jackson, Adrian; Maddison, James R.: Adapting and optimising fluidity for high-fidelity coastal modelling (2018)
  14. Kalantzis, Vassilis; Xi, Yuanzhe; Saad, Yousef: Beyond automated multilevel substructuring: domain decomposition with rational filtering (2018)
  15. Kovkov, D. V.; Lemtyuzhnikova, D. V.: Decomposition in multidimensional Boolean-optimization problems with sparse matrices (2018)
  16. Sawant, Saurabh S.; Tumuklu, Ozgur; Jambunathan, Revathi; Levin, Deborah A.: Application of adaptively refined unstructured grids in DSMC to shock wave simulations (2018)
  17. Breedveld, Sebastiaan; van den Berg, Bas; Heijmen, Ben: An interior-point implementation developed and tuned for radiation therapy treatment planning (2017)
  18. Fu, Lin; Hu, Xiangyu Y.; Adams, Nikolaus A.: A physics-motivated centroidal Voronoi particle domain decomposition method (2017)
  19. Haddar, Houssem; Jiang, Zixian; Riahi, Mohamed Kamel: A robust inversion method for quantitative 3D shape reconstruction from coaxial eddy current measurements (2017)
  20. Li, Ruipeng; Saad, Yousef: Low-rank correction methods for algebraic domain decomposition preconditioners (2017)

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