About Stefano Zampini Stefano Zampini Senior Research Scientist, Hierarchical Computations on Manycore Architectures High Performance Computing Domain Decomposition Scientific Machine Learning Parallel and Distributed Computing computational science and engineering As a computational mathematician and software engineer, Stefano Zampini's work lies at the intersection of numerical analysis, predictive simulations, and high-performance computing, with recent forays into machine learning. Articles Related News September 2020 H2Opus: a Performance-Oriented Library for Hierarchical Matrices 1 min read · Wed, Sep 16 2020 News GPU Computing High Performance Computing numerical linear algebra H2Opus: a Performance-Oriented Library for Hierarchical Matrices Download at https://github.com/ecrc/h2opus. Experience our latest HPC software release that implements H 2-Matrix operations on shared-memory systems, possibly equipped with GPU hardware accelerators. The prime target applications for H2Opus are PDE-constrained optimizations. The features of H2Opus include: Generation of matrix structure from a point set and admissibility condition, Construction of a hierarchical matrix given a kernel function, Matrix-vector and matrix-multiple-vector multiplication, Basis orthogonalization
H2Opus: a Performance-Oriented Library for Hierarchical Matrices 1 min read · Wed, Sep 16 2020 News GPU Computing High Performance Computing numerical linear algebra H2Opus: a Performance-Oriented Library for Hierarchical Matrices Download at https://github.com/ecrc/h2opus. Experience our latest HPC software release that implements H 2-Matrix operations on shared-memory systems, possibly equipped with GPU hardware accelerators. The prime target applications for H2Opus are PDE-constrained optimizations. The features of H2Opus include: Generation of matrix structure from a point set and admissibility condition, Construction of a hierarchical matrix given a kernel function, Matrix-vector and matrix-multiple-vector multiplication, Basis orthogonalization
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