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- Moritz Kreutzer, Georg Hager, Gerhard Wellein, Holger Fehske, Alan R. Bishop
- SIAM J. Scientific Computing
- 2014

Sparse matrix-vector multiplication (spMVM) is the most time-consuming kernel in many numerical algorithms and has been studied extensively on all modern processor and accelerator architectures. However, the optimal sparse matrix data storage format is highly hardware-specific, which could become an obstacle when using heterogeneous systems. Also, it is as… (More)

The dynamical density-matrix renormalization group (DDMRG) method is a numerical technique for calculating the zero-temperature dynamical properties in low-dimensional quantum many-body systems. For the one-dimensional Hubbard model and its extensions, DDMRG allows for accurate calculations of these properties for lattices with hundreds of sites and… (More)

- Gerald Schubert, Holger Fehske, Georg Hager, Gerhard Wellein
- Parallel Processing Letters
- 2011

We evaluate optimized parallel sparse matrix-vector operations for several representative application areas on widespread multicore-based cluster configurations. First the single-socket baseline performance is analyzed and modeled with respect to basic architectural properties of standard multicore chips. Beyond the single node, the performance of parallel… (More)

- Gerhard Wellein, Georg Hager, Thomas Zeiser, Markus Wittmann, Holger Fehske
- 2009 33rd Annual IEEE International Computer…
- 2009

We present a pipelined wavefront parallelization approach for stencil-based computations. Within a fixed spatial domain successive wavefronts are executed by threads scheduled to a multicore processor chip with a shared outer level cache. By re-using data from cache in the successive wavefronts this multicore-aware parallelization strategy employs temporal… (More)

- Moritz Kreutzer, Georg Hager, Gerhard Wellein, Holger Fehske, Alan R. Bishop
- ArXiv
- 2013

Sparse matrix-vector multiplication (spMVM) is the most time-consuming kernel in many numerical algorithms and has been studied extensively on all modern processor and accelerator architectures. However, the optimal sparse matrix data storage format is highly hardware-specific, which could become an obstacle when using heterogeneous systems. Also, it is as… (More)

- Moritz Kreutzer, Georg Hager, Gerhard Wellein, Holger Fehske, Achim Basermann, Alan R. Bishop
- 2012 IEEE 26th International Parallel and…
- 2012

Sparse matrix-vector multiplication (spMVM) is the dominant operation in many sparse solvers. We investigate performance properties of spMVM with matrices of various sparsity patterns on the nVidia "Fermi" class of GPGPUs. A new "padded jagged diagonals storage" (pJDS) format is proposed which may substantially reduce the memory overhead intrinsic to the… (More)

- Andreas Alvermann, Holger Fehske
- J. Comput. Physics
- 2011

We critically discuss the stability of edge states and edge magnetism in zigzag edge graphene nanoribbons (ZGNRs). We point out that magnetic edge states might not exist in real systems and show that there are at least three very natural mechanisms—edge reconstruction, edge passivation, and edge closure—which dramatically reduce the effect of edge states in… (More)

- Gerhard Wellein, Georg Hager, Achim Basermann, Holger Fehske
- VECPAR
- 2002

- M Bonitz, V S Filinov, V E Fortov, P R Levashov, H Fehske
- Physical review letters
- 2005

The analysis of Coulomb crystallization is extended from one-component to two-component plasmas. Critical parameters for the existence of Coulomb crystals are derived for both classical and quantum crystals. In the latter case, a critical mass ratio of the two charged components is found, which is of the order of 80. Thus, holes in semiconductors with… (More)