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A massively parallel combination technique for the solution of high-dimensional PDEs.

M. Heene. University of Stuttgart, Germany, (2018)

Doktorvater / Doktormutter: Dirk Pflüger
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Autor_in: Mario Heene
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Andere Publikationen
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Load-Balancing for Large-Scale Soot Particle Agglomeration Simulations(2020)

S. Hirschmann, A. Kronenburg, C. Glass, und D. Pflüger. IOS Press

Learning-Based Load Balancing for Massively Parallel Simulations of Hot Fusion Plasmas(2020)

T. Pollinger, und D. Pflüger. IOS Press

Evaluation of Pool-Based Testing Approaches to Enable Population-wide Screening for COVID-19(2020)

T. de Wolff, D. Pflüger, M. Rehme, J. Heuer, und M. Bittner.

Enabling unstructured domain decompositions for inhomogeneous short-range molecular dynamics in ESPResSo(2019)

S. Hirschmann, C. Glass, und D. Pflüger. Springer Nature

Harnessing billions of tasks for a scalable portable hydrodynamic simulation of the merger of two stars.(2019)

T. Heller, B. Adelstein-Lelbach, K. Huck, J. Biddiscombe, P. Grubel, A. Koniges, M. Kretz, D. Marcello, D. Pfander, A. Serio, F. Seinstra, G. Clayton, D. Pflüger, D. Eder, und H. Kaiser.

Developing coarse-grained models for agglomerate growth(2019)

M. Smiljanic, R. Weeber, D. Pflüger, C. Holm, und A. Kronenburg.

B-Splines on Sparse Grids for Surrogates in Uncertainty Quantification(2019)

M. Rehme, F. Franzelin, und D. Pflüger. Elsevier

Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario(2019)

M. Köppel, F. Franzelin, I. Kröker, S. Oladyshkin, G. Santin, D. Wittwar, A. Barth, B. Haasdonk, W. Nowak, D. Pflüger, und C. Rohde. Springer

From Piz Daint to the Stars: Simulation of Stellar Mergers using High-Level Abstractions.(2019)

G. Daiß, P. Amini, J. Biddiscombe, P. Diehl, J. Frank, K. Huck, H. Kaiser, D. Marcello, D. Pfander, und D. Pflüger.

Heterogeneous Distributed Big Data Clustering on Sparse Grids.(2019)

D. Pfander, G. Daiß, und D. Pflüger.

Load-balancing and hybrid parallelization for simulations with large particle numbers(2018)

S. Hirschmann, C. Glass, und D. Pflüger.

Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario(2018)

M. Koeppel, F. Franzelin, I. Kröker, S. Oladyshkin, G. Santin, D. Wittwar, A. Barth, B. Haasdonk, W. Nowak, D. Pflüger, und C. Rohde.

Scalable Algorithmic Detection of Silent Data Corruption for High-Dimensional PDEs(2018)

A. Hinojosa, H. Bungartz, und D. Pflüger. Springer

Load-Balancing and Spatial Adaptivity for Coarse-Grained Molecular Dynamics Applications.(2018)

S. Hirschmann, M. Lahnert, C. Schober, M. Brunn, M. Mehl, und D. Pflüger. Springer

Limiting Ranges of Function Values of Sparse Grid Surrogates(2018)

F. Franzelin, und D. Pflüger. Springer

Towards a coarse-grained approach of nanoparticle agglomeration(2018)

M. Smiljanic, A. Kronenburg, R. Weeber, C. Holm, und D. Pflüger.

Visualization of fracture progression in peridynamics(2017)

M. Bussler, P. Diehl, D. Pflüger, S. Frey, F. Sadlo, T. Ertl, und M. Schweitzer. Elsevier

Pricing multidimensional financial derivatives with stochastic volatilities using the dimensional-adaptive combination technique(2017)

J. Benk, und D. Pflüger. Incisive Media

Langevin Dynamics Simulation of Transport and Aggregation of Soot Nano-particles in Turbulent Flows(2017)

G. Inci, A. Kronenburg, R. Weeber, und D. Pflüger. Springer

Load balancing with p4est for Short-Range Molecular Dynamics with ESPResSo(2017)

M. Brunn, C. Glass, M. Lahnert, M. Mehl, und D. Pflüger. IOS Press

Towards understanding optimal load balancing of heterogeneous short-range molecular dynamics(2016)

S. Hirschmann, C. Glass, und D. Pflüger. Workshop on High Performance Computing and Big Data in Molecular Engineering 2016 (HBME)

Recent Developments in the Theory and Application of the Sparse Grid Combination Technique.(2016)

M. Hegland, B. Harding, C. Kowitz, D. Pflüger, und P. Strazdins. Springer

A massively-parallel, fault-tolerant solver for high-dimensional PDEs(2016)

M. Heene, A. Hinojosa, H. Bungartz, und D. Pflüger.

Global communication schemes for the numerical solution of high-dimensional PDEs.(2016)

P. Hupp, M. Heene, R. Jacob, und D. Pflüger.

Selected Recent Applications of Sparse Grids(2015)

B. Peherstorfer, C. Kowitz, D. Pflüger, und H. Bungartz. Cambridge Univ. Press

Gradient-based optimization with hierarchical B-splines on sparse grids(2015)

J. Valentin, und D. Pflüger.

Towards a fault-tolerant, scalable implementation of GENE(2015)

A. Parra Hinojosa, C. Kowitz, M. Heene, D. Pflüger, und H. Bungartz. Springer

Efficient and scalable distributed-memory hierarchization algorithms for the sparse grid combination technique.(2015)

M. Heene, und D. Pflüger. IOS Press

Load Balancing for Massively Parallel Computations with the Sparse Grid Combination Technique.(2014)

M. Heene, C. Kowitz, und D. Pflüger.

Application of Machine Learning Techniques to the Re-ranking of Search Results(2004)

M. Buchholz, D. Pflüger, und J. Poon. Springer-Verlag

Andere Publikationen gleichnamiger Autoren
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Jahr
Titel
Autor(en)

Non-intrusive uncertainty quantification with sparse grids for multivariate peridynamic simulations(2015)

F. Franzelin, P. Diehl, und D. Pflüger. Springer

Efficient and scalable distributed-memory hierarchization algorithms for the sparse grid combination technique(2016)

M. Heene, und D. Pflüger. IOS Press

Data mining on vast data sets as a cluster system benchmark(2016)

A. Heinecke, R. Karlstetter, D. Pflüger, und H. Bungartz. Wiley-Blackwell

AutoTuneTMP: Auto-Tuning in C++ With Runtime Template Metaprogramming.(2018)

D. Pfander, M. Brunn, und D. Pflüger. IEEE Computer Society

Hierarchical Extended B-splines for Approximations on Sparse Grids(2018)

M. Rehme, und D. Pflüger. Springer

AutoTuneTMP: Auto-Tuning in C++ With Runtime Template Metaprogramming.(2018)

D. Pfander, M. Brunn, und D. Pflüger. IEEE Computer Society