Refereed publications from HPCTools

  1. Implicit-explicit Runge-Kutta methods for stiff combustion problems. Erik Lindblad, Damir M. Valiev, Bernhard Müller, Jarmo Rantakokko, Per Lötstedt, and Michael A. Liberman. In Shock Waves: Volume 1, pp 299-304, Springer-Verlag, Berlin, 2009. (DOI).
  2. Geographical locality and dynamic data migration for OpenMP implementations of adaptive PDE solvers. Markus Nordén, Henrik Löf, Jarmo Rantakokko, and Sverker Holmgren. In OpenMP Shared Memory Parallel Programming, volume 4315 of Lecture Notes in Computer Science, pp 382-393, Springer-Verlag, Berlin, 2008. (DOI).
  3. Grid-enabling an efficient algorithm for demanding global optimization problems in genetic analysis. Mahen Jayawardena and Sverker Holmgren. In Proc. 3rd International Conference on e-Science and Grid Computing, pp 205-212, IEEE, Piscataway, NJ, 2007. (DOI).
  4. Using parallel computing and grid systems for genetic mapping of quantitative traits. Mahen Jayawardena, Kajsa Ljungberg, and Sverker Holmgren. In Applied Parallel Computing: State of the Art in Scientific Computing, volume 4699 of Lecture Notes in Computer Science, pp 627-636, Springer-Verlag, Berlin, 2007. (DOI).
  5. Dynamic data migration for structured AMR solvers. Markus Nordén, Henrik Löf, Jarmo Rantakokko, and Sverker Holmgren. In International journal of parallel programming, volume 35, pp 477-491, 2007. (DOI).
  6. Study of load balancing strategies for finite element computations on heterogeneous clusters. Kalyani Munasinghe and Richard Wait. In Applied Parallel Computing: State of the Art in Scientific Computing, volume 3732 of Lecture Notes in Computer Science, pp 1123-1130, Springer-Verlag, Berlin, 2006. (DOI).
  7. Analyzing advanced PDE solvers through simulation. Henrik Johansson, Dan Wallin, and Sverker Holmgren. In Applied Parallel Computing: State of the Art in Scientific Computing, volume 3732 of Lecture Notes in Computer Science, pp 893-900, Springer-Verlag, Berlin, 2006. (DOI).
  8. Design and usability of a PDE solver framework for curvilinear coordinates. Malin Ljungberg, Kurt Otto, and Michael Thuné. In Advances in Engineering Software, volume 37, pp 814-825, 2006. (DOI).
  9. Software design for finite difference schemes based on index notation. Krister Åhlander and Kurt Otto. In Future generations computer systems, volume 22, pp 102-109, 2006. (DOI).
  10. Multigrid and Gauss-Seidel smoothers revisited: Parallelization on chip multiprocessors. Dan Wallin, Henrik Löf, Erik Hagersten, and Sverker Holmgren. In Proc. 20th ACM International Conference on Supercomputing, pp 145-155, ACM Press, New York, 2006. (DOI).
  11. Designing for geometrical symmetry exploitation. André Yamba Yamba, Krister Åhlander, and Malin Ljungberg. In Scientific Programming, volume 14, pp 61-80, 2006. (External link).
  12. Implicit-explicit Runge-Kutta method for combustion simulation. Erik Lindblad, Damir M. Valiev, Bernhard Müller, Jarmo Rantakokko, Per Lötstedt, and Michael A. Liberman. In Proc. ECCOMAS CFD Conference 2006, p 20, Tech. Univ. Delft, The Netherlands, 2006.
  13. Algorithmic optimizations of a conjugate gradient solver on shared memory architectures. Henrik Löf and Jarmo Rantakokko. In International Journal of Parallel, Emergent and Distributed Systems, volume 21, pp 345-363, 2006. (DOI).
  14. OpenMP versus MPI for PDE solvers based on regular sparse numerical operators. Markus Nordén, Sverker Holmgren, and Michael Thuné. In Future generations computer systems, volume 22, pp 194-203, 2006. (DOI).
  15. Sorting out the relationships between pairs of iterators, values, and references. Krister Åhlander. In Generative Programming and Component Engineering, volume 3676 of Lecture Notes in Computer Science, pp 342-356, Springer-Verlag, Berlin, 2005. (DOI).
  16. Load balancing by changing the graph connectivity on heterogeneous clusters. Kalyani Munasinghe and Richard Wait. In Advances in Grid Computing – EGC 2005, volume 3470 of Lecture Notes in Computer Science, pp 1040-1047, Springer-Verlag, Berlin, 2005. (DOI).
  17. Sparse matrix storage revisited. Malik Silva and Richard Wait. In Computing Frontiers: 2005, pp 230-235, ACM Press, New York, 2005. (DOI).
  18. affinity-on-next-touch: Increasing the Performance of an Industrial PDE Solver on a cc-NUMA System. Henrik Löf and Sverker Holmgren. In Proc. 19th ACM International Conference on Supercomputing, pp 387-392, ACM Press, New York, 2005. (DOI).
  19. A Dynamic MPI-OpenMP Model for Structured Adaptive Mesh Refinement. Jarmo Rantakokko. In Parallel Processing Letters, volume 15, pp 37-47, 2005.
  20. Comparison of parallelization models for structured adaptive mesh refinement. Jarmo Rantakokko. In Euro-Par 2004: Parallel Processing, volume 3149 of Lecture Notes in Computer Science, pp 615-623, Springer-Verlag, Berlin, 2004. (DOI).
  21. Generic programming aspects of symmetry exploiting numerical software. Malin Ljungberg and Krister Åhlander. In Proc. ECCOMAS Congress 2004, p 20, Jyväskylä, Finland, 2004. (Fulltext).
  22. Improving Geographical Locality of Data for Shared Memory Implementations of PDE Solvers. Henrik Löf, Markus Nordén, and Sverker Holmgren. In Computational Science – ICCS 2004, volume 3037 of Lecture Notes in Computer Science, pp 9-16, Springer-Verlag, Berlin, 2004. (DOI).
  23. Characterization of a hybrid and dynamic partitioner for SAMR applications. Henrik Johansson and Johan Steensland. In Proc. Parallel and Distributed Computing and Systems: 2004, pp 713-718, ACTA Press, Calgary, Canada, 2004.
  24. Cache memory behavior of advanced PDE solvers. Dan Wallin, Henrik Johansson, and Sverker Holmgren. In Parallel Computing: Software Technology, Algorithms, Architectures and Applications, volume 13 of Advances in Parallel Computing, pp 475-482, Elsevier, Amsterdam, The Netherlands, 2004.
  25. Algorithm visualization through animation and role plays. Jarmo Rantakokko. In Proc. Third Program Visualization Workshop, volume 407 of Research Report, pp 76-81, Dept. of Computer Science, University of Warwick, 2004.
  26. THROOM — Supporting POSIX Multithreaded Binaries on a Cluster. Henrik Löf, Zoran Radović, and Erik Hagersten. In Euro-Par 2003: Parallel Processing, volume 2790 of Lecture Notes in Computer Science, pp 760-769, Springer-Verlag, Berlin, 2003. (DOI).
  27. Evaluating the educational impact of visualization. Thomas Naps, Guido Rößling, Jay Anderson, Stephen Cooper, Wanda Dann, Rudolf Fleischer, Boris Koldehofe, Ari Korhonen, Marja Kuittinen, Charles Leska, Lauri Malmi, Myles McNally, Jarmo Rantakokko, and Rockford J. Ross. In SIGCSE Bulletin inroads, volume 35, number 4, pp 124-136, 2003. (DOI).
  28. Cache aware data laying for the Gauss-Seidel smoother. Malik Silva. In Electronic Transactions on Numerical Analysis, volume 15, pp 66-77, 2003.
  29. Supporting tensor symmetries in EinSum. Krister Åhlander. In Computers and Mathematics with Applications, volume 45, pp 789-803, 2003. (DOI).
  30. Parallelization of an unstructured finite volume solver for the Maxwell equations. Jarmo Rantakokko and Fredrik Edelvik. In Parallel Computing: Advances and Current Issues, pp 213-221, Imperial College Press, London, 2002.
  31. Go for both types of cache locality!. Malik Silva and Richard Wait. In Proc, volume 2002:2 of HPC Asia, pp 500-503, Tata McGraw-Hill, New Delhi, India, 2002.
  32. Load balancing in scientific computing on clusters. Kalyani Munasinghe and Richard Wait. In Proc. Int. Workshop on Grid and Cooperative Computing, pp 281-288, Publishing House of Electronics Industry, Beijing, China, 2002.
  33. Increasing resolution and forecast length with a parallel ocean model. Tomas Wilhelmsson, Josef Schüle, Jarmo Rantakokko, and Lennart Funkquist. In Operational Oceanography: Implementation at the European and Regional Scales, volume 66 of Elsevier Oceanography Series, pp 77-85, Elsevier Science, Amsterdam, The Netherlands, 2002.
  34. An application-centric characterization of domain-based SFC partitioners for parallel SAMR. Johan Steensland, Sumir Chandra, and Manish Parashar. In IEEE Transactions on Parallel and Distributed Systems, volume 13, pp 1275-1289, 2002. (DOI).
  35. On object-oriented frameworks and coordinate free formulations of PDEs. Krister Åhlander, Magne Haveraaen, and Hans Munthe-Kaas. In Engineering with Computers, volume 18, pp 286-294, 2002. (DOI).
  36. Performance of PDE solvers on a self-optimizing NUMA architecture. Sverker Holmgren, Markus Nordén, Jarmo Rantakokko, and Dan Wallin. In Parallel Algorithms and Applications, volume 17, pp 285-299, 2002. (DOI).
  37. Einstein summation for multidimensional arrays. Krister Åhlander. In Computers and Mathematics with Applications, volume 44, pp 1007-1017, 2002. (DOI).
  38. Optimal parameter values for a parallel structured adaptive mesh refinement algorithm. Michael Thuné and Stefan Söderberg. In Applied Parallel Computing: New Paradigms for HPC in Industry and Academia, volume 1947 of Lecture Notes in Computer Science, pp 177-186, Springer-Verlag, Berlin, 2001. (DOI).
  39. A comparison of partitioning schemes for blockwise parallel SAMR algorithms. Johan Steensland, Stefan Söderberg, and Michael Thuné. In Applied Parallel Computing: New Paradigms for HPC in Industry and Academia, volume 1947 of Lecture Notes in Computer Science, pp 160-169, Springer-Verlag, Berlin, 2001. (DOI).
  40. A local refinement algorithm for data partitioning. Jarmo Rantakokko. In Applied Parallel Computing: New Paradigms for HPC in Industry and Academia, volume 1947 of Lecture Notes in Computer Science, pp 140-148, Springer-Verlag, Berlin, 2001. (DOI).
  41. Efficiency of a hybrid method for the wave equation. Larisa Beilina, Klas Samuelsson, and Krister Åhlander. In Finite Element Methods: Three-dimensional problems, volume 15 of GAKUTO Internat. Ser. Math. Sci. Appl., pp 9-21, Gakkotosho, Tokyo, 2001.
  42. On the role of mathematical abstractions for scientific computing. Krister Åhlander, Magne Haveraaen, and Hans Z. Munthe-Kaas. In The Architecture of Scientific Software, pp 145-158, Kluwer Academic Publishers, Norwell, MA, 2001.
  43. Object-oriented modeling of parallel PDE solvers. Michael Thuné, Krister Åhlander, Malin Ljungberg, Markus Nordén, Kurt Otto, and Jarmo Rantakokko. In The Architecture of Scientific Software, pp 159-174, Kluwer Academic Publishers, Norwell, MA, 2001.
  44. Discrete element models of particle flows. Richard Wait. In Mathematical Modelling and Analysis, volume 6, pp 156-164, 2001.
  45. Three-dimensional variational data assimilation for a limited area model, Part II: Observation handling and assimilation experiments. Magnus Lindskog, Nils Gustafsson, Beatriz Navascués, Kristian S. Mogensen, Xiang-Yu Huang, Xiaohua Yang, Ulf Andræ, Loïk Berre, Sigurdur Thorsteinsson, and Jarmo Rantakokko. In Tellus. Series A, Dynamic meteorology and oceanography, volume 53, pp 447-468, 2001. (DOI).
  46. Mixed C<sub>++</sub>/Fortran 90 implementation of parallel flow solvers. Malin Ljungberg and Michael Thuné. In Parallel Computational Fluid Dynamics: Trends and Applications, pp 233-240, Elsevier Science, Amsterdam, The Netherlands, 2001. (DOI).
  47. An integrated decomposition and partitioning approach for irregular block-structured applications. Jarmo Rantakokko. In Parallel and Distributed Processing, volume 1800 of Lecture Notes in Computer Science, pp 485-496, Springer-Verlag, Berlin, 2000. (DOI).
  48. Partitioning strategies for structured multiblock grids. Jarmo Rantakokko. In Parallel Computing, volume 26, pp 1661-1680, 2000. (DOI).
  49. Characterization of domain-based partitioners for parallel SAMR applications. Johan Steensland, Michael Thuné, Sumir Chandra, and Manish Parashar. In Proc. Parallel and Distributed Computing and Systems: 2000, pp 425-430, ACTA Press, Calgary, Canada, 2000.
  50. Comparison of partitioning strategies for PDE solvers on multiblock grids. Jarmo Rantakokko. In Applied Parallel Computing: Large Scale Scientific and Industrial Problems, volume 1541 of Lecture Notes in Computer Science, pp 468-475, Springer-Verlag, Berlin, 1998. (DOI).
  51. Software tools for partitioning block-structured applications. Jarmo Rantakokko. In Computing in Object-Oriented Parallel Environments, volume 1505 of Lecture Notes in Computer Science, pp 83-94, Springer-Verlag, Berlin, 1998. (DOI).
  52. A framework for partitioning structured grids with inhomogeneous workload. Jarmo Rantakokko. In Parallel Algorithms and Applications, volume 13, pp 135-151, 1998. (DOI).
  53. Object-oriented software tools for the construction of preconditioners. Eva Mossberg, Kurt Otto, and Michael Thuné. In Scientific Programming, volume 6, pp 285-295, 1997. (External link).
  54. Object-Oriented Construction of Parallel PDE Solvers. Michael Thuné, Eva Mossberg, Peter Olsson, Jarmo Rantakokko, Krister Åhlander, and Kurt Otto. In Modern Software Tools for Scientific Computing, pp 203-226, Birkhäuser, Boston, MA, 1997.
  55. Partitioning strategies for composite grids. Michael Thuné. In Parallel Algorithms and Applications, volume 11, pp 325-348, 1997. (DOI).
  56. Strategies for parallel variational data assimilation. Jarmo Rantakokko. In Parallel Computing, volume 23, pp 2017-2039, 1997. (DOI).
  57. Towards an expressive language for PDE solvers. Michael Thuné and Krister Åhlander. In Programming Languages and Systems, volume 1058 of Lecture Notes in Computer Science, pp 373-386, Springer-Verlag, Berlin, 1996. (DOI).
  58. Software tools for parallel CFD on composite grids. Peter Olsson, Jarmo Rantakokko, and Michael Thuné. In Parallel Computational Fluid Dynamics: Implementations and Results Using Parallel Computers, pp 725-732, Elsevier Science, Amsterdam, The Netherlands, 1996. (DOI).
  59. Object-oriented software tools for parallel PDE solvers. Michael Thuné. In Wuhan University Journal of Natural Sciences, volume 1, pp 420-429, 1996. (DOI).
  60. A partitioning algorithm for composite grids. Michael Thuné. In Parallel Algorithms and Applications, volume 1, pp 69-81, 1993. (DOI).
  61. Portability and data structures in scientific computing: Object-oriented design of utility routines in Fortran. Kjell Högström and Michael Thuné. In Parallel Computing: From Theory to Sound Practice, pp 585-588, IOS Press, Amsterdam, The Netherlands, 1992.
  62. The partitioning problem for a class of data parallel algorithms. Michael Thuné. In Parallel Computing, volume 18, pp 867-878, 1992. (DOI).
  63. Straightforward partitioning of composite grids for explicit difference methods. Michael Thuné. In Parallel Computing, volume 17, pp 665-672, 1991. (DOI).
  64. A partitioning strategy for explicit difference methods. Michael Thuné. In Parallel Computing, volume 15, pp 147-154, 1990. (DOI).
  65. A numerical algorithm for stability analysis of difference methods for hyperbolic systems. Michael Thuné. In SIAM Journal on Scientific and Statistical Computing, volume 11, pp 63-81, 1990. (DOI).
  66. Partition shapes for explicit difference methods: slices vs rectangles. Michael Thuné. In Hypercube and Distributed Computers, pp 383-384, Elsevier Science, Amsterdam, The Netherlands, 1989.
  67. Stability of a Runge–Kutta method for the Euler equations on a substructured domain. Kurt Otto and Michael Thuné. In SIAM Journal on Scientific and Statistical Computing, volume 10, pp 154-174, 1989. (DOI).
  68. Automatic GKS stability analysis. Michael Thuné. In SIAM Journal on Scientific and Statistical Computing, volume 7, pp 959-977, 1986. (DOI).
  69. A software package for stability analysis of difference methods. Michael Thuné. In PDE Software: Modules, Interfaces and Systems, pp 89-102, Elsevier Science, Amsterdam, The Netherlands, 1984.