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Ing. Daniel Langr

Research Projects Parallel Algorithms for Sparse Matrices
Research Interests parallel algorithms, sparse matrices, memory optimal formats for sparse matrices, sparse matrix visualization, C++ metaprogramming
Education Czech Technical University in Prague, Faculty of Electrical Engineering
Skills C++, MPI, HPC, Generic Programming, Metaprograming
Czech, English
Recent Publications  
Langr, D., et al., Fake run-time selection of template arguments in C++ Lecture Notes in Computer Science, 7304, p.p. 140-154, 2012.
 Langr D., et al., Adaptive-Blocking Hierarchical Storage Format for Sparse Matrices
In Proceedings of FedCSIS'12, p.p. 545-551, 2012.
Significant Publications
Draayer, J.P., et al., Symmetry-adapted no-core shell model applications for light nuclei with QCD-inspired interactions Progress in Particle and Nuclear Physics, 67(2), p.p. 516-520, 2012.