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- Dirk Pflüger
- 2010

The curse of dimensionality, i.e. the exponential dependency of the overall computational effort on the number of dimensions, is still a roadblock for the numerical treatment of high-dimensional problems, where “high” typically ranges from five to several hundred dimensions. Especially data-driven problems are challenging due to the ever-increasing size,… (More)

- Dirk Pflüger, Benjamin Peherstorfer, Hans-Joachim Bungartz
- J. Complexity
- 2010

- Daniel Butnaru, Dirk Pflüger, Hans-Joachim Bungartz
- ICCS
- 2011

With the ever-increasing complexity, accuracy, dimensionality, and size of simulations, a step in the direction of data-intensive scientific discovery becomes necessary. Parameter-dependent simulations are an example of such a data-intensive tasks: The researcher, who is interested in the dependency of the simulation’s result on a set of input parameters,… (More)

- Benjamin Peherstorfer, Dirk Pflüger, Hans-Joachim Bungartz
- Australasian Conference on Artificial…
- 2011

- Alexander Heinecke, Dirk Pflüger
- Conf. Computing Frontiers
- 2011

Gaining knowledge out of vast datasets is a main challenge in data-driven applications nowadays. Sparse grids provide a numerical method for both classification and regression in data mining which scales only linearly in the number of data points and is thus well-suited for huge amounts of data. Due to the recursive nature of sparse grid algorithms, they… (More)

- Alexander Heinecke, Michael Klemm, Dirk Pflüger, Arndt Bode, Hans-Joachim Bungartz
- Euro-Par Workshops
- 2011

The sparse grid discretization technique enables a compressed representation of higher-dimensional functions. In its original form, it relies heavily on recursion and complex data structures, thus being far from well-suited for GPUs. In this paper, we describe optimizations that enable us to implement compression and decompression, the crucial sparse grid… (More)

- Hans-Joachim Bungartz, Alexander Heinecke, Dirk Pflüger, Stefanie Schraufstetter
- 2010 IEEE International Symposium on Parallel…
- 2010

We present the parallelization of a sparse grid finite element discretization of the Black-Scholes equation, which is commonly used for option pricing. Sparse grids allow to handle higher dimensional options than classical approaches on full grids, and can be extended to a fully adaptive discretization method. We introduce the algorithmical structure of… (More)

- Alexander Heinecke, Dirk Pflüger
- International Journal of Parallel Programming
- 2012

Gaining knowledge out of vast datasets is a main challenge in data-driven applications nowadays. Sparse grids provide a numerical method for both classification and regression in data mining which scales only linearly in the number of data points and is thus well-suited for huge amounts of data. Due to the recursive nature of sparse grid algorithms and… (More)

- Janos Benk, Dirk Pflüger
- 2012 International Conference on High Performance…
- 2012

This paper presents an efficient approach to parallel pricing of multi-dimensional financial derivatives based on the Black-Scholes Partial Differential Equation (BS-PDE). One of the main challenges for such multi-dimensional problems is the curse of dimensionality, that is tackled in our approach by the combination technique (CT). This technique consists… (More)