activity
20072022
most citedNew Row-grouped CSR format for storing the sparse matrices on GPU with implementation in CUDA

37 citations · 73 across the 7 of their papers we have counts for

collaborators

7 papers

math.OC2022★ 1 cited

Numerical Optimization of the Dirichlet Boundary Condition in the Phase Field Model with an Application to Pure Substance Solidification

Aleš Wodecki, Pavel Strachota, Tomáš Oberhuber +2

As opposed to the distributed control of parabolic PDE's, very few contributions currently exist pertaining to the Dirichlet boundary condition control for parabolic PDE's. This mo…

stat.ML2020★ 3 cited

Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations

Tomas Pevny, Vasek Smidl, Martin Trapp +2

In this work, we propose Sum-Product-Transform Networks (SPTN), an extension of sum-product networks that uses invertible transformations as additional internal nodes. The type and…

nucl-th2015★ 26 cited

Electron-scattering form factors for 6Li in the ab initio symmetry-guided framework

T. Dytrych, A. C. Hayes, K. D. Launey +5

We present an ab initio symmetry-adapted no-core shell-model description for Li. We study the structure of the ground state of Li and the impact of the symmetry-guided…

cs.DC2012★ 6 cited

Adaptive Row-grouped CSR Format for Storing of Sparse Matrices on GPU

Martin Heller, Tomáš Oberhuber

We present new adaptive format for storing sparse matrices on GPU. We compare it with several other formats including CUSPARSE which is today probably the best choice for processin…

math.NA2011

Numerical solution for the anisotropic Willmore flow of graphs

Tomas Oberhuber

The Willmore flow is well known problem from the differential geometry. It minimizes the Willmore functional defined as integral of the mean-curvature square over given manifold. F…

cs.DC2010★ 37 cited

New Row-grouped CSR format for storing the sparse matrices on GPU with implementation in CUDA

Tomáš Oberhuber, Atsushi Suzuki, Jan Vacata

In this article we present a new format for storing sparse matrices. The format is designed to perform well mainly on the GPU devices. We present its implementation in CUDA. The pe…