Bruno Lang
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View article: Modeling Minimum Cost Network Flows With Port‐Hamiltonian Systems
Modeling Minimum Cost Network Flows With Port‐Hamiltonian Systems Open
We give a short overview of advantages and drawbacks of the classical formulation of minimum cost network flow problems and solution techniques, to motivate a reformulation of classical static minimum cost network flow problems as optimal …
View article: A new perspective on dynamic network flow problems via port-Hamiltonian systems
A new perspective on dynamic network flow problems via port-Hamiltonian systems Open
We suggest a global perspective on dynamic network flow problems that takes advantage of the similarities to port-Hamiltonian dynamics. Dynamic minimum cost flow problems are formulated as open-loop optimal control problems for general por…
View article: Modeling Minimum Cost Network Flows With Port-Hamiltonian Systems
Modeling Minimum Cost Network Flows With Port-Hamiltonian Systems Open
We give a short overview of advantages and drawbacks of the classical formulation of minimum cost network flow problems and solution techniques, to motivate a reformulation of classical static minimum cost network flow problems as optimal …
View article: Efficient Dominance Filtering for Unions and Minkowski Sums of Non-Dominated Sets
Efficient Dominance Filtering for Unions and Minkowski Sums of Non-Dominated Sets Open
View article: Efficient Parallel Reduction of Bandwidth for Symmetric Matrices
Efficient Parallel Reduction of Bandwidth for Symmetric Matrices Open
View article: Quartic multifractality and finite-size corrections at the spin quantum Hall transition
Quartic multifractality and finite-size corrections at the spin quantum Hall transition Open
The spin quantum Hall transition (or class C transition in two dimensions) represents one of the few localization-delocalization transitions for which some of the critical exponents are known exactly. Not known, however, is the multifracta…
View article: Flexible subspace iteration with moments for an effective contour integration-based eigensolver
Flexible subspace iteration with moments for an effective contour integration-based eigensolver Open
Contour integration schemes are a valuable tool for the solution of difficult interior eigenvalue problems. However, the solution of many large linear systems with multiple right hand sides may prove a prohibitive computational expense. Th…
View article: Self-consistent-field ensembles of disordered Hamiltonians: Efficient solver and application to superconducting films
Self-consistent-field ensembles of disordered Hamiltonians: Efficient solver and application to superconducting films Open
Our general interest is in self-consistent-field (scf) theories of disordered\nfermions. They generate physically relevant sub-ensembles ("scf-ensembles")\nwithin a given Altland-Zirnbauer class. We are motivated to investigate such\nensem…
View article: Verified Quadrature in Determining Newton's Constant of Gravitation
Verified Quadrature in Determining Newton's Constant of Gravitation Open
View article: Network Simulation for Pedestrian Flows with HyDEFS
Network Simulation for Pedestrian Flows with HyDEFS Open
The reliable simulation of pedestrian movement is an essential tool for the security aware design and analysis of buildings and infrastructure. We developed HyDEFS, an event-driven dynamic flow simulation software which is designed to simu…
View article: On the equivalence of the Hermitian eigenvalue problem and hypergraph edge elimination
On the equivalence of the Hermitian eigenvalue problem and hypergraph edge elimination Open
It is customary to identify sparse matrices with the corresponding adjacency or incidence graph. For the solution of linear systems of equations using Gaussian elimination, the representation by its adjacency graph allows a symbolic comput…
View article: Hypergraph edge elimination - A symbolic phase for Hermitian eigensolvers based on rank-1 modifications
Hypergraph edge elimination - A symbolic phase for Hermitian eigensolvers based on rank-1 modifications Open
It is customary to identify sparse matrices with the corresponding adjacency or incidence graphs. For the solution of a linear system of equations using Gaussian elimination, the representation by its adjacency graph allows a symbolic fact…
View article: Computational challenges in materials science
Computational challenges in materials science Open
This dissertation sets out to improve performance—in terms of runtime as well as accuracy—of Materials Science simulations by means of custom kernels. The approach for each of our use-cases can be summarized as follows: We present some ins…
View article: ESSEX: Equipping Sparse Solvers For Exascale
ESSEX: Equipping Sparse Solvers For Exascale Open
The ESSEX project has investigated programming concepts, data structures, and numerical algorithms for scalable, efficient, and robust sparse eigenvalue solvers on future heterogeneous exascale systems. Starting without the burden of legac…
View article: Equipping Sparse Solvers for Exascale
Equipping Sparse Solvers for Exascale Open
View article: ELPA: A Parallel Solver for the Generalized Eigenvalue Problem1
ELPA: A Parallel Solver for the Generalized Eigenvalue Problem1 Open
For symmetric (hermitian) (dense or banded) matrices the computation of eigenvalues and eigenvectors Ax = λBx is an important task, e.g. in electronic structure calculations. If a larger number of eigenvectors are needed, often direct solv…
View article: Parallel eigenvalue computation for banded generalized eigenvalue problems
Parallel eigenvalue computation for banded generalized eigenvalue problems Open
View article: Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects
Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects Open
View article: Equipping Sparse Solvers for Exascale (ESSEX / ESSEX II)
Equipping Sparse Solvers for Exascale (ESSEX / ESSEX II) Open
The ESSEX project is funded by the German DFG priority programme 1648 "Software for Exascale Computing" (SPPEXA). In 2016 it has entered its second funding phase, ESSEX-II.
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\n ESSEX investigated programming concepts and numerical algori…
View article: Benefits from using mixed precision computations in the ELPA-AEO and\n ESSEX-II eigensolver projects
Benefits from using mixed precision computations in the ELPA-AEO and\n ESSEX-II eigensolver projects Open
We first briefly report on the status and recent achievements of the ELPA-AEO\n(Eigenvalue Solvers for Petaflop Applications - Algorithmic Extensions and\nOptimizations) and ESSEX II (Equipping Sparse Solvers for Exascale) projects.\nIn bo…
View article: Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects
Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects Open
We first briefly report on the status and recent achievements of the ELPA-AEO (Eigenvalue Solvers for Petaflop Applications - Algorithmic Extensions and Optimizations) and ESSEX II (Equipping Sparse Solvers for Exascale) projects. In both …
View article: Convergence of integration-based methods for the solution of standard and generalized Hermitian eigenvalue problems
Convergence of integration-based methods for the solution of standard and generalized Hermitian eigenvalue problems Open
Recently, methods based on spectral projection and numerical integration have been proposed in the literature as candidates for reliable high-performance eigenvalue solvers. The key ingredients of this type of eigenvalue solver are a Rayle…
View article: Algorithmic Developments and Software Engineering for Scalable Sparse Eigensolvers in the DFG Project ESSEX
Algorithmic Developments and Software Engineering for Scalable Sparse Eigensolvers in the DFG Project ESSEX Open
In the German Research Foundation (DFG) project ESSEX (Equipping Sparse Solvers for Exascale), we develop scalable sparse eigensolver libraries for large quantum physics problems. Partners in ESSEX are the Universities of Erlangen, Greifsw…
View article: High-performance implementation of Chebyshev filter diagonalization for interior eigenvalue computations
High-performance implementation of Chebyshev filter diagonalization for interior eigenvalue computations Open
View article: Efficient subspace iteration with Chebyshev-type filtering
Efficient subspace iteration with Chebyshev-type filtering Open
Shift-invert and other methods for computing inner eigenvalues often require the solution of linear systems. This may become a problem if the linear systems are very ill-conditioned and the matrix dimension precludes the use
\nof direct so…