Peter Zaspel

Dr. Peter Zaspel

Assistent / PostDoc (FG Harbrecht)


Spiegelgasse 1
4051 Basel


Tel.: +41 61 207 24 16


Submitted Manuscripts

  • H. Harbrecht and P. Zaspel. A scalable H-matrix approach for the solution of boundary integral equations on multi-GPU clusters. Preprint 2018-11, Fachbereich Mathematik, Universität Basel, Switzerland, 2018. Also available as arXiv:1806.11558.

  • P. Zaspel. Analysis and parallelization strategies for Ruge-Stüben AMG on many-core processors, Preprint 2017-06, Fachbereich Mathematik, Universität Basel, Switzerland, 2017.



  • M. Griebel, Ch. Rieger, P. Zaspel. Kernel-based stochastic collocation for the random two-phase Navier-Stokes equations. Accepted for publication in International Journal for Uncertainty Quantification, April 2019; also available as arXiv:1810.11270.

  • P. Zaspel. Ensemble Kalman filters for reliability estimation in perfusion inference. International Journal for Uncertainty Quantification, 9(1):15-32, 2019; also available as arXiv:1810.09290.

  • P. Zaspel, B. Huang, H. Harbrecht, O. A. von Lilienfeld. Boosting quantum machine learning models with multi-level combination technique: Pople diagrams revisited. Journal of Chemical Theory and Computation, 15(3):1546-1559, 2019; also available as arXiv:1808.02799.

  • H. Harbrecht, P. Zaspel. On the algebraic construction of sparse multilevel approximations of elliptic tensor product problems. Journal of Scientific Computing, Springer, 78(2):1272-1290, 2019; also available as Preprint 2018-01, Fachbereich Mathematik, Universität Basel, Switzerland, 2018 and as arXiv:1801.10532.

  • P. Zaspel. Algorithmic patterns for H matrices on many-core processors. Journal of Scientific Computing, Springer, 78(2):1174-1206, 2019; also available as Preprint 2017-12, Fachbereich Mathematik, Universität Basel, Switzerland, 2017 and as arXiv:1708.09707 preprint.

  • P. Zaspel. Subspace correction methods in algebraic multi-level frames. Linear Algebra and its Applications, Vol. 488(1),  Jan. 2016, pp. 505-521.

  • D. Pflüger, H.-J. Bungartz, M. Griebel, F. Jenko, T. Dannert, M. Heene, A. Parra Hinojosa, C. Kowitz and P. Zaspel: EXAHD: An Exa-scalable Two-Level Sparse Grid Approach for Higher-Dimensional Problems in Plasma Physics and Beyond. In: Lopes L. et al. (eds) Euro-Par 2014: Parallel Processing Workshops. Euro-Par 2014. Lecture Notes in Computer Science, vol 8806. Springer, Cham, 2014.

  • P. Zaspel and M. Griebel. Solving incompressible two-phase flows on multi-GPU clusters. Computer & Fluids, 80(0):356 - 364, 2013.

  • P. Zaspel and M. Griebel. Massively parallel fluid simulations on Amazon's HPC cloud. In Network Cloud Computing and Applications (NCCA), 2011 First International Symposium on, pages 73 -78, Nov. 2011.

  • P. Zaspel and M. Griebel. Photorealistic visualization and fluid animation: coupling of Maya with a two-phase Navier-Stokes fluid solver. Computing and Visualization in Science, 14(8):371-383, 2011.

  • M. Griebel and P. Zaspel. A multi-GPU accelerated solver for the three-dimensional two-phase incompressible Navier-Stokes equations. Computer Science - Research and Development, 25(1-2):65-73, May 2010.

Edited Volumes

  • V. Heuveline, M. Schick, C. Webster, P. Zaspel. Uncertainty Quantification and High Performance Computing, Dagstuhl Reports, Vol. 6, Issue 9, pp. 59-73.


  • hmglib: hierarchical matrices on graphic processing units (github)

  • MPLA: multi-GPU parallel library for dense iterative matrix solvers (github)

  • Multi-GPU support und uncertainty quantification for two-phase Navier Stokes (NaSt3DGPF)



As Lecturer:

Invited Talks

  • "Multifidelity kernel-based approximation by the combination technique”, Minisymposium "Multifidelity methods for uncertainty quantification and optimization in complex systems", ICIAM 2019, Valencia, Spain, July 15-19, 2019, on invite by John Jakeman, PhD.

  • "Kernel-based stochastic collocation for Navier-Stokes", Minisymposium "Theory and Practice of meshless Fluid-Simulations", ICIAM 2019, Valencia, Spain, July 15-19, 2019, on invite by PD Dr. Christian Rieger.

  • "Towards multi-fidelity machine learning in scientific computing on GPU clusters", Seminar of the Faculty of Informatics, USI Lugano, Lugano, Switzerland, March 6, 2019, on invite by Prof. Dr. Michael Multerer.

  • "Augmenting the explanatory power of predictions by uncertainty quantification",
    2nd Workshop on Embedded Machine Learning - WEML2018, Heidelberg University, November 8, 2018.

  • "Meshfree and multi-index approximations for parametric real-world problems",
    Seminar on Uncertainty Quantification, RWTH Aachen, Aachen, Germany, August 29, 2018.

  • "Optimal-complexity kernel-based stochastic collocation with applications in fluid mechanics", Seminar of the "Mathematics in Computational Science and Engineering" group, EPFL Lausanne, Switzerland, October 24, 2017, on invitation by Prof. Dr. Fabio Nobile.

  • "Scalable solvers for meshless methods on many-core clusters", QUIET 2017 - Quantification of Uncertainty: Improving Efficiency and Technology, SISSA, International School for Advanced Studies, Trieste, Italy, 18-21 July 2017.

  • "Algorithmic patterns for hierarchical matrices on many-core processors", Seminar in Numerical Analysis, University of Basel, September 18, 2016, on invitation by Prof. Dr. Helmut Harbrecht.

  • "H-matrices on many-core hardware with applications in parametric PDE's", Colloquium of the Faculty of Engineering, University of Kiel, December 9, 2016, on invitation by Prof. Dr. Steffen Börm.

All other talks

Dr. Peter Zaspel

Assistant / Postdoc (Computational Mathematics)


Spiegelgasse 1
4051 Basel