Dr. rer. nat. Dirk Pflüger

Address:

TU München

Institut für Informatik

Boltzmannstr. 3

85748 Garching b. München

Office:

MI 02.05.043

Email:

Phone:

(089) 289 18 613

Fax:

(089) 289 18 607

Office Hours:

by arrangement

News

I am now Juniorprofessor in the Cluster of Excellence "Simulation Technologies" (SimTech) in Stuttgart, see my new website.

Software

SG++, a toolkit for the solution of high-dimensional problems with (spatially adaptive) sparse grids.

Projects/Links

• TUM-IAS Focus Group HPC
• BMBF SIMDATA-NL - Non-Linear Characterization and Analysis of FEM Simulation Results for Motor-Car Components and Crash Tests
• KAUST-partnership Virtual Arabia

Books

• J. Garcke and D. Pflüger (ed.): Sparse Grids and Applications - Munich 2012 [BibTeX], Volume 97 of Lecture Notes in Computational Science and Engineering. Springer International Publishing, 2014.
• H.-J. Bungartz, S. Zimmer, M. Buchholz and D. Pflüger: Modeling and Simulation - An Application-Oriented Introduction [BibTeX]. Springer-Verlag, Berlin, October 2013.
• H.-J. Bungartz, S. Zimmer, M. Buchholz and D. Pflüger: Modellbildung und Simulation: Eine anwendungsorientierte Einführung [BibTeX]. Springer-Verlag, Berlin, October 2013. 2. überarb. Aufl.
• D. Pflüger: Spatially Adaptive Sparse Grids for High-Dimensional Problems [pdf] [BibTeX]. Verlag Dr. Hut, München, August 2010.
• H.-J. Bungartz, S. Zimmer, M. Buchholz and D. Pflüger: Modellbildung und Simulation: Eine anwendungsorientierte Einführung [BibTeX]. Springer-Verlag, Berlin, March 2009.

Publications

Volume 2018

• M. Heene, A. Parra Hinojosa, M. Obersteiner, H.-J. Bungartz and D. Pflüger: EXAHD: An Exa-Scalable Two-Level Sparse Grid Approach for Higher-Dimensional Problems in Plasma Physics and Beyond [BibTeX].
  In W. Nagel, D. Kröner and M. Resch (ed.), High Performance Computing in Science and Engineering ' 17, p. 513–529. Springer-Verlag, March 2018.
• I.-G. Farcas, P.-C. Sarbu, H.-J. Bungartz, T. Neckel and B. Uekermann: Multilevel adaptive stochastic collocation with dimensionality reduction [BibTeX].
  In J. Garcke, D. Pflüger, C. G. Webster and G. Zhang (ed.), Sparse Grids and Applications - Miami 2016, Volume 123 of Lecture Notes in Computational Science and Engineering, p. 43––68. Springer International Publishing, 2018.

Volume 2017

• M. Obersteiner, A. Parra Hinojosa, M. Heene, H.-J. Bungartz and D. Pflüger: A Highly Scalable, Algorithm-Based Fault-Tolerant Solver for Gyrokinetic Plasma Simulations [pdf] [BibTeX].
  In ScalA '17: Proceedings of the 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, November 2017.
• A. Parra Hinojosa, H.-J. Bungartz and D. Pflüger: Scalable Algorithmic Detection of Silent Data Corruption for High-Dimensional PDEs [BibTeX].
  In Sparse Grids and Applications 2016, 2017. Accepted.

Volume 2016

• M. Heene, A. Parra Hinojosa, H.-J. Bungartz and D. Pflüger: A Massively-Parallel, Fault-Tolerant Solver for Time-Dependent PDEs in High Dimensions [BibTeX].
  In Euro-Par 2016, June 2016. Accepted.
• V. Khakhutskyy and M. Hegland: Spatially-Dimension-Adaptive Sparse Grids for Online Learning [BibTeX].
  In D. Pflüger and J. Garcke (ed.), Sparse Grids and Applications - Stuttgart 2014, Volume 109 of LNCSE, p. 133–162. Springer International Publishing, March 2016.
• A. Heinecke, R. Karlstetter, D. Pflüger and H.-J. Bungartz: Data Mining on Vast Datasets as a Cluster System Benchmark [BibTeX].
  In Concurrency and Computation: Practice and Experience, Volume 28(7), p. 2145–2165. John Wiley & Sons, 2016. submitted.

Volume 2015

• B. Peherstorfer, C. Kowitz, D. Pflüger and H.-J. Bungartz: Selected Recent Applications of Sparse Grids [] [BibTeX].
  In Numerical Mathematics: Theory, Methods and Applications, Volume 8(01), p. 47–77. Cambridge Journals, February 2015.
• A. Parra Hinojosa, C. Kowitz, M. Heene, D. Pflüger and H.-J. Bungartz: Towards a fault-tolerant, scalable implementation of GENE [BibTeX].
  In Proceedings of ICCE 2014 of Lecture Notes in Computational Science and Engineering. Springer-Verlag, 2015. Accepted.

Volume 2014

• 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 [BibTeX].
  In Euro-Par 2014: Parallel Processing Workshops of Lecture Notes in Computer Science. Springer-Verlag, September 2014. accepted.
• P. Hupp, R. Jacob, M. Heene, D. Pflüger and M. Hegland: Global Communication Schemes for the Sparse Grid Combination Technique [BibTeX].
  In M. Bader, H.-J. Bungartz, A. Bode, M Gerndt and G.R. Joubert (ed.), Parallel Computing: Accelerating Computational Science and Engineering (CSE), Volume 25 of Advances in Parallel Computing, p. 564––573. IOS Press, Amsterdam, March 2014.
• M. Heene, C. Kowitz and D. Pflüger: Load Balancing for Massively Parallel Computations with the Sparse Grid Combination Technique [BibTeX].
  In M. Bader, H.-J. Bungartz, A. Bode, M Gerndt and G.R. Joubert (ed.), Parallel Computing: Accelerating Computational Science and Engineering (CSE), Volume 25 of Advances in Parallel Computing, p. 574––583. IOS Press, Amsterdam, March 2014.
• V. Khakhutskyy, D. Pflüger and M. Hegland: Scalability and Fault Tolerance of the Alternating Direction Method of Multipliers for Sparse Grids [BibTeX].
  In M. Bader, H.-J. Bungartz, A. Bode, M Gerndt and G.R. Joubert (ed.), Parallel Computing: Accelerating Computational Science and Engineering (CSE), Volume 25 of Advances in Parallel Computing, p. 603––612. IOS Press, Amsterdam, March 2014.
• V. Khakhutskyy and D. Pflüger: Alternating Direction Method of Multipliers for Hierarchical Basis Approximators [BibTeX].
  In J. Garcke and D. Pflüger (ed.), Sparse Grids and Applications - Munich 2012, Volume 97 of Lecture Notes in Computational Science and Engineering, p. 221––238. Springer International Publishing, 2014.
• C. Kowitz and M. Hegland: An Opticom Method for Computing Eigenpairs [BibTeX].
  In J. Garcke and D. Pflüger (ed.), Sparse Grids and Applications - Munich 2012, Volume 97(10) of Lecture Notes in Computational Science and Engineering, p. 239–253. Springer International Publishing, 2014.
• B. Peherstorfer, F. Franzelin, D. Pflüger and H.-J. Bungartz: Classification with Probability Density Estimation on Sparse Grids [BibTeX].
  In J. Garcke and D. Pflüger (ed.), Sparse Grids and Applications - Munich 2012, Volume 97 of Lecture Notes in Computational Science and Engineering, p. 255––270. Springer International Publishing, 2014.
• G. Buse, D. Pflüger and R. Jacob: Efficient Pseudorecursive Evaluation Schemes for Non-Adaptive Sparse Grids [BibTeX].
  In J. Garcke and D. Pflüger (ed.), Sparse Grids and Applications - Munich 2012, Volume 97 of Lecture Notes in Computational Science and Engineering, p. 1–27. Springer International Publishing, 2014.
• F. Franzelin, P. Diehl, D. Pflüger and M. A. Schweitzer: Non-intrusive uncertainty quantification with sparse grids for multivariate peridynamic simulations [BibTeX].
  In M. Griebel and M. A. Schweitzer (ed.), Meshfree Methods for Partial Differential Equations VII, Volume 100 of Lecture Notes in Computational Science and Engineering, 2014. accepted.

Volume 2013

• B. Peherstorfer, J. Adorf, D. Pflüger and H.-J. Bungartz: Image Segmentation with Adaptive Sparse Grids [BibTeX].
  In Proceedings of 26th Australasian Joint Conference on Artificial Intelligence. Springer, September 2013.
• A. Heinecke and D. Pflüger: Emerging Architectures Enable to Boost Massively Parallel Data Mining using Adaptive Sparse Grids [BibTeX].
  In International Journal of Parallel Programming, Volume 41(3), p. 357–399. Springer US, New York, June 2013.
• A. Heinecke, D. Pflüger, D. Budnikov, M. Klemm, A. Narkis, M. Shevtsov and A. Zaks: Demonstrating Performance Portability of A Custom OpenCL Data Mining Application to the Intel(R) Xeon Phi(TM) Coprocessor [BibTeX].
  In International Workshop on OpenCL Proceedings 2013, May 2013. accepted for publication.

Volume 2012

• D. Butnaru, B. Peherstorfer, D. Pflüger and H.-J. Bungartz: Fast Insight into High-Dimensional Parametrized Simulation Data [pdf] [BibTeX].
  In 11th International Conference on Machine Learning and Applications (ICMLA). IEEE, Boca Raton, Florida, December 2012.
• B. Peherstorfer, D. Pflüger and H.-J. Bungartz: Clustering Based on Density Estimation with Sparse Grids [BibTeX].
  In KI 2012: Advances in Artificial Intelligence, Volume 7526 of Lecture Notes in Computer Science. Springer, October 2012.
• D. Pflüger: Spatially Adaptive Refinement [pdf] [BibTeX].
  In J. Garcke and M. Griebel (ed.), Sparse Grids and Applications of Lecture Notes in Computational Science and Engineering, p. 243–262. Springer, Berlin Heidelberg, October 2012.
• C. Kowitz, D. Pflüger, F. Jenko and M. Hegland: The Combination Technique for the Initial Value Problem in Linear Gyrokinetics [BibTeX].
  In M. Griebel and J. Garcke (ed.), Sparse Grids and Applications, Volume 88 of Lecture Notes in Computational Science and Engineering, p. 205–222. Springer, Heidelberg, October 2012.
• J. Benk and D. Pflüger: Hybrid Parallel Solutions of the Black-Scholes PDE with the Truncated Combination Technique [pdf] [BibTeX].
  In Proceedings of the HPCS conference, July 2012.
• A. Heinecke, B. Peherstorfer, D. Pflüger and Z. Song: Sparse Grid Classifiers as Base Learners for AdaBoost [BibTeX].
  In 2012 International Conference on High Performance Computing and Simulation (HPCS),, p. 161–166. IEEE, Madrid, July 2012.
• G. Buse, R. Jacob, D. Pflüger and A. Murarasu: A Non-static Data Layout Enhancing Parallelism and Vectorization in Sparse Grid Algorithms [BibTeX].
  In Proceeding of the 11th International Symposium on Parallel and Distributed Computing - ISPDC 2012. IEEE, Munich, June 2012.
• A. Murarasu, G. Buse, J. Weidendorfer, D. Pflüger and A. Bode: fastsg: A Fast Routines Library for Sparse Grids [BibTeX].
  In Proceedings of the International Conference on Computational Science, ICCS 2012 of Procedia Computer Science, June 2012.
• D. Butnaru, G. Buse and D. Pflüger: A Parallel and Distributed Surrogate Model Implementation for Computational Steering [pdf] [BibTeX].
  In Proceeding of the 11th International Symposium on Parallel and Distributed Computing - ISPDC 2012. IEEE, Munich, June 2012.
• A. Heinecke, M. Klemm, D. Pflüger, A. Bode and H.-J. Bungartz: Extending a Highly Parallel Data Mining Algorithm to the Intel(R) Many Integrated Core Architecture [BibTeX].
  In Euro-Par 2011: Parallel Processing Workshops: Proceedings of the 4th Workshop on UnConventional High Performance Computing 2011 (UCHPC 2011), Volume 7156/2012 of Lecture Notes in Computer Science, p. 375–384. Springer, Bordeaux, France, May 2012.
• A. Heinecke, M. Klemm, H. Pabst and D. Pflüger: Towards high-performance implementations of a custom HPC kernel using Intel(R) Array Building Blocks [BibTeX].
  In Facing the Multicore-Challenge II, Volume 7174 of Lecture Notes in Computer Science, p. 36–47. Springer, Berlin, May 2012.
• H.-J. Bungartz, A. Heinecke, D. Pflüger and S. Schraufstetter: Parallelizing a Black-Scholes solver based on finite elements and sparse grids [BibTeX].
  In Concurrency and Computation: Practice and Experience. John Wiley & Sons, Ltd, March 2012.

Volume 2011

• B. Peherstorfer, D. Pflüger and H.-J. Bungartz: A Sparse-Grid-Based Out-of-Sample Extension for Dimensionality Reduction and Clustering with Laplacian Eigenmaps [BibTeX].
  In D. Wang and M. Reynolds (ed.), AI 2011: Advances in Artificial Intelligence, Volume 7106 of Lecture Notes in Computer Science, p. 112–121. Springer, Berlin Heidelberg, December 2011.
• H.-J. Bungartz, A. Heinecke, D. Pflüger and S. Schraufstetter: Option Pricing with a Direct Adaptive Sparse Grid Approach [BibTeX].
  In Journal of Computational and Applied Mathematics, Volume 236(15), p. 3741 –– 3750, October 2011. online Okt. 2011.
• D. Butnaru, D. Pflüger and H.-J. Bungartz: Towards High-Dimensional Computational Steering of Precomputed Simulation Data using Sparse Grids [pdf] [BibTeX].
  In Proceedings of the International Conference on Computational Science (ICCS) 2011, Volume 4 of Procedia CS, p. 56–65. Springer-Verlag, June 2011.
• A. Heinecke and D. Pflüger: Multi- and Many-Core Data Mining with Adaptive Sparse Grids [BibTeX].
  In Proceedings of the 8th ACM International Conference on Computing Frontiers, p. 29:1–29:10. ACM, New York, USA, May 2011.
• A. Murarasu, J. Weidendorfer, G. Buse, D. Butnaru and D. Pflüger: Compact Data Structure and Scalable Algorithms for the Sparse Grid Technique [] [BibTeX].
  In Proceedings of the 16th ACM symposium on Principles and practice of parallel programming of PPoPP '11, p. 25–34. ACM, New York, NY, USA, February 2011.

Volume 2010

• D. Pflüger, B. Peherstorfer and H.-J. Bungartz: Spatially adaptive sparse grids for high-dimensional data-driven problems [BibTeX].
  In Journal of Complexity, Volume 26(5), p. 508––522. Academic Press, Inc., Orlando, FL, USA, October 2010. published online April 2010.
• M. Frommert, D. Pflüger, T. Riller, M. Reinecke, H.-J. Bungartz and T. Enßlin: Efficient cosmological parameter sampling using sparse grids [BibTeX].
  Volume 406(2) of Monthly Notices of the Royal Astronomical Society, p. 1177––1189. Wiley-Blackwell, August 2010. online April 2010.
• D. Pflüger: Spatially Adaptive Sparse Grids for High-Dimensional Problems [pdf] [BibTeX].
  Dissertation, Institut für Informatik, Technische Universität München. Verlag Dr. Hut, München, February 2010.
• H.-J. Bungartz, A. Heinecke, D. Pflüger and S. Schraufstetter: Parallelizing a Black-Scholes Solver based on Finite Elements and Sparse Grids [BibTeX].
  In IEEE International Parallel & Distributed Processing Symposium, 2010.

Volume 2008

• H.-J. Bungartz, D. Pflüger and S. Zimmer: Adaptive Sparse Grid Techniques for Data Mining [pdf] [BibTeX].
  In H.G. Bock, E. Kostina, X.P. Hoang and R. Rannacher (ed.), Modelling, Simulation and Optimization of Complex Processes 2006, Proc. Int. Conf. HPSC, Hanoi, Vietnam, p. 121–130. Springer-Verlag, August 2008.

Volume 2007

• D. Pflüger, I. L. Muntean and H.-J. Bungartz: Adaptive Sparse Grid Classification Using Grid Environments [pdf] [BibTeX].
  In Y. Shi, D. van Albada, J. Dongarra and P. Sloot (ed.), ICCS 2007, Volume 4487(1) of LNCS, p. 708–715. Springer, Berlin Heidelberg, May 2007.

Volume 2005

• D. Pflüger: Data Mining mit Dünnen Gittern [pdf] [BibTeX].
  No. 2264.
  Diplomarbeit, IPVS, Universität Stuttgart, March 2005.

Volume 2004

• M. Buchholz, D. Pflüger and J. Poon: Application of Machine Learning Techniques to the Re-ranking of Search Results [BibTeX].
  In S. Biundo, T. Frühwirth and G. Palm (ed.), KI 2004: Advances in Artificial Intelligence, Volume 3238 of Lecture Notes in Computer Science, p. 67–81. Springer-Verlag, September 2004.

Talks

• A Highly Scalable, Fault-Tolerant Implementation of the Sparse Grid Combination Technique [BibTeX].
  SGA2018, Garching, July 2018.
• A Highly Scalable, Fault-Tolerant Implementation of the Sparse Grid Combination Technique [BibTeX].
  PASC18, Basel, July 2018.
• An Algorithm-Based Fault-Tolerant Framework for High-dimensional PDEs [BibTeX].
  SIAM Conference on Parallel Processing for Scientific Computing 2018, Tokyo, March 2018.
• A Highly Scalable, Algorithm-Based Fault-Tolerant Solver for Gyrokinetic Plasma Simulations [BibTeX].
  ScalA'17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Denver, Colorado, November 2017.
• EXAHD - An Exa-Scalable Two-Level Sparse Grid Approach for Higher-Dimensional Problems in Plasma Physics and Beyond [BibTeX].
  High Performance Computing in Science & Engineering - 20th Results and Review Workshop of the HLRS, Stuttgart, HLRS, October 2017.
• A Highly-Scalable, Algorithm-Based Fault-Tolerant Solver for Gyrokinetic Plasma Simulations [BibTeX].
  ParCo 2017, Bologna, September 2017.
• Classification with Density Estimation on Sparse Grids [BibTeX].
  SIAM Conference on Computational Science and Engineering, Boston, February 2013.
• Sparse Grid Data Mining for Approximating High-dimensional Functions [BibTeX].
  SIAM Conference on Computational Science and Engineering, Boston, February 2013.
• Adaptive Sparse Grids and the Curse of Dimensionality [BibTeX].
  Seminar Multiscale Modeling & Simulation, Cluster of Excellence Engineering of Advanced Materials, FAU Erlangen, February 2013.
• Efficient High-Dimensional Regularization in the Sparse Grid Basis [BibTeX].
  5th Workshop in High-Dimensional Approximation, Australian National University, Canberra, February 2013.
• Sparse Grids and Applications: Coping with the Curse of Dimensionality [BibTeX].
  Colloquium, SimTech Cluster of Excellence, Universität Stuttgart, January 2013.
• Simulation, Software and HPC: A Tale of Parameter-Dependent Simulations and High Dimensionalities [BibTeX].
  Annual meeting industrial consortium SimTech, Universität Stuttgart, November 2012.
• Sparse Grids [BibTeX].
  Ferienakademie, Reinswald, Sarntal, October 2012.
• SG++ -- Software for Spatially Adaptive Sparse Grids [BibTeX].
  2nd Workshop on Sparse Grids and Applications, IAS, Technische Universität München, July 2012.
• A Non-static Data Layout Enhancing Parallelism and Vectorization in Sparse Grid Algorithms [BibTeX].
  ISPDC 2012, Garching, June 2012.
• Einführung in Python [BibTeX].
  inf.misc, Universität Stuttgart, May 2012.
• Efficient Regularization and Parallelization for Sparse Grid Regression [BibTeX].
  SIAM Conference on Applied Linear Algebra, Valencia, May 2012.
• Sparse Grids and HPC: Perspectives for High-Dimensional Discretizations [BibTeX].
  Scalable Hierarchical Algorithms for eXtreme Computing, KAUST, April 2012.
• A Sparse-Grid-Based Out-of-Sample Extension for Dimensionality Reduction and Clustering with Laplacian Eigenmaps [BibTeX].
  24th Australasian Conference on Artificial Intelligence, Perth, December 2011.
• Spatially Adaptive Sparse Grids for Data-Driven Problems [BibTeX].
  Computational Mathematics Seminar, CMA, ANU, Canberra, October 2011.
• Classification and Regression with Sparse Grids [BibTeX].
  Ferienakademie, Durnholz, September 2011.
• Spatially adaptive sparse grid regression [BibTeX].
  4th Workshop on High-Dimensional Approximation, Universität Bonn, June 2011.
• Problem-Adapted Spatially Adapted Sparse Grids [BibTeX].
  Workshop on Sparse Grids and Applications, Hausdorf Research Institute, Bonn, May 2011.
• Sparse Grids---High-Dimensional Functions in Data Mining and Beyond [BibTeX].
  2nd Coding Days, KAUST, Thuwal, Saudi-Arabia, April 2011.
• Spatially Adaptive Sparse Grids for Data Mining and Parameter Estimation [BibTeX].
  Seminar ModNumDiff, Matheon, TU Berlin, November 2010.
• Clustering [BibTeX].
  Kickoff-Meeting BMBF Projekt SIMDATA-NL, Bonn, October 2010.
• Adaptive, Sparse, and Grids [BibTeX].
  Ferienakademie, Durnholz, September 2010.
• Parallelizing a Black-Scholes Solver based on Finite Elements and Sparse Grids [BibTeX].
  Parallel and Distributed Computing in Finance (PDCoF) at IEEE IPDPS, Atlanta, USA, April 2010.
• Dünne Gitter: Hochdimensionale Numerik im Data Mining [BibTeX].
  Seminar, IBB, Helmholtz Zentrum München, May 2009.
• Approximation of Non-Smooth Functions with Spatially Adaptive Sparse Grids in Classification Tasks [BibTeX].
  High Dimensional Approximation (HDA) 09, University of New South Wales, Sydney, Australia, February 2009.
• Dünne Gitter: Hochdimensionale Numerik in Data Mining, Astrophysik und Finanzanwendungen [BibTeX].
  Doktorandenforum Natur und Wissenschaft, Studienstiftung des deutschen Volkes, Borken-Gemen, April 2008.
• Classification with spatially adaptive sparse grids: Towards high dimensional problems [BibTeX].
  DFG Kolloquium, Bonn, April 2008.
• Tackling Higher Dimensions in Data Mining Using Adaptive Sparse Grids [pdf] [BibTeX].
  Nonlinear and Adaptive Approximation in High Dimensions, Physikzentrum Bad Honnef, December 2007.
• Adaptive Sparse Grid Classification Using Grid Environments [BibTeX].
  International Conference on Computational Science (ICCS) 2007, Beijing, China, May 2007.
• Data Mining mit Dünnen Gittern [BibTeX].
  Doktorandenforum Natur und Wissenschaft, Studienstiftung des deutschen Volkes, Wittenberg, April 2007.
• Sparse grid techniques for Data Mining [BibTeX].
  Seminar of the Machine Learning and Data Mining in Bioinformatics Group, Chair for Bioinformatics, TU München, November 2006.
• Adaptive Sparse Grid Techniques for Data Mining [BibTeX].
  HPSC 2006, Institute of Mathematics, Vietnamese Academy of Science and Technology, Hanoi, Vietnam, March 2006.
• Application of Machine Learning Techniques to the Re-ranking of Search Results [BibTeX].
  Jahrestagung Künstliche Intelligenz, KI 2004, Universität Ulm, September 2004.

Students

• A. Parra Hinojosa: A Massively-Parallel, Fault-Tolerant Solver for Time-Dependent PDEs in High Dimensions [BibTeX].
  Euro-Par 2016, Grenoble, August 2016.
• A. Parra Hinojosa: Tolerating Hard & Soft Faults with the Sparse Grid Combination Technique [BibTeX].
  ISC 2016 PhD Forum, Frankfurt, June 2016. (Poster).
• A. Parra Hinojosa: Towards a fault-tolerant, scalable implementation of GENE [BibTeX].
  ICCE 2014, Universität Stuttgart, October 2014.
• A. Parra Hinojosa: Overcoming the fault tolerance (exa)challenge using sparse grids in plasma physics simulations [BibTeX].
  Sparse Grids and Applications, Universität Stuttgart, September 2014.
• S. Kinauer: Hierarchische Optimierung mit Dünnen Gittern [pdf] [BibTeX].
  Studienarbeit/SEP/IDP, Fakultät für Mathematik, Technische Universität München, September 2013.
• A. Gillert: Parallelization of Peak-Matching Algorithms for Comprehensive Two-Dimensional Gas Chromatography Coupled to Mass Spectrometry [BibTeX].
  Bachelor's thesis, Institut für Informatik, Technische Universität München, October 2012.
• J. Klein: Modellierung und Implementierung von automatisierten Dispositions-Vorschlägen [BibTeX].
  Master's thesis, Institut für Informatik, Technische Universität München, October 2011.
• D. Wang: Sparse Grid Combination Technique for Regression Problems in Finance [BibTeX].
  Master's thesis, Institut für Informatik, Technische Universität München, September 2011.
• K. Röhner: Polynomial Basis Functions on Adaptive Sparse Grids [pdf] [BibTeX].
  Bachelor's thesis, Institut für Informatik, Technische Universität München, August 2011.
• A. Heinecke: Integration von Adaptivität in einen Dünngitterlöser für Basket-Optionen [pdf] [BibTeX].
  Master's thesis, Institut für Informatik, Technische Universität München, February 2011.
• N. Melik-Barkhudarov: Spatially Adaptive Semi-Supervised Learning [BibTeX].
  Master's thesis, Institut für Informatik, Technische Universität München, September 2010.
• R. Röttger: Integration of Prewavelet Ansatz Functions into SG++ [pdf] [BibTeX].
  Studienarbeit/SEP/IDP, Institut für Informatik, Technische Universität München, September 2010.
• M. Müller: Konzeption und Implementierung einer C2X-basierten dynamischen Routenführung für die mikroskopische Verkehrssimulation VISSIM [pdf] [BibTeX].
  Bachelor's thesis, Institut für Informatik, Technische Universität München, September 2010.
• A. Heinecke: Realisierung einer Randbehandlung für adaptive Dünngittermethoden mit Anwendungen im Data Mining und in der Finanzmathematik [pdf] [BibTeX].
  Diplomarbeit, Institut für Informatik, Technische Universität München, February 2010.
• J. Blank: Numerische Quadratur von hochdimensionalen Verteilungsfunktionen mit adaptiven Dünnen Gittern [BibTeX].
  Studienarbeit/SEP/IDP, Institut für Informatik, Technische Universität München, October 2009. IDP.
• J. Hölzl: Automatischer Korrektheitsbeweis von Algorithmen zur Hierarchischen Basistransformation [BibTeX].
  Studienarbeit/SEP/IDP, Fakultät für Informatik, Technische Universität München, January 2009. IDP.
• B. Cankurt, Ö. Demirel, Y. Li, D. Mudigere and K. Rahnema: Inverted Pendulum Control Demonstrator [BibTeX].
  Studienarbeit/SEP/IDP, Institut für Informatik, Technische Universität München, January 2009. BGCE project.
• M. Wunsch: Halbüberwachtes Lernen mit raumadaptiven dünnen Gittern [BibTeX].
  No. 2763.
  Diplomarbeit, IPVS, Universität Stuttgart, November 2008.
• D. Pandey: Regression with Spatially Adaptive Sparse Grids in Financial Applications [BibTeX].
  Master's thesis, Fakultät für Informatik, Technische Universität München, September 2008.
• C. Bohn, A. Landschoof and M. Ostertag: Planung und Entwicklung einer Online Bibel mit Web 2.0 Elementen [BibTeX].
  Studienarbeit/SEP/IDP, Institut für Informatik, Technische Universität München, May 2008. SEP.
• M. Salaterski: Storing Results of Parameterized CFD Simulations Using Sparse-Grid Techniques [BibTeX].
  Master's thesis, Fakultät für Informatik, Technische Universität München, May 2008.
• L. Johansson: Einsatz der Dünngitterklassifikation für Benchmark-Probleme [pdf] [BibTeX].
  Diplomarbeit, Fakultät für Informatik, Technische Universität München, April 2008.
• J. Blank and R. Röttger: Data Mining mit Dünnen Gittern [BibTeX].
  Studienarbeit/SEP/IDP, Fakultät für Informatik, Technische Universität München, January 2008. SEP.
• J. Benk, F. Moufatich and D. Pandey: Theta Fitter - Financial Model Fitter [BibTeX].
  Studienarbeit/SEP/IDP, Fakultät für Informatik, Technische Universität München, January 2008. BGCE project.
• F. Prasser and A. Hristov: Erstellung eines umfangreichen Tools zur Audiobearbeitung [pdf] [BibTeX].
  Studienarbeit/SEP/IDP, Fakultät für Informatik, Technische Universität München, January 2007.