Zobrazeno 1 - 10
of 4 251
pro vyhledávání: '"Computer Science - Mathematical Software"'
Autor:
Joshy, Anugrah Jo, Hwang, John T.
Recent advances in computing hardware and modeling software have given rise to new applications for numerical optimization. These new applications occasionally uncover bottlenecks in existing optimization algorithms and necessitate further specializa
Externí odkaz:
http://arxiv.org/abs/2410.12942
Autor:
Croci, M., Wells, G. N.
In this paper we develop the first fine-grained rounding error analysis of finite element (FE) cell kernels and assembly. The theory includes mixed-precision implementations and accounts for hardware-acceleration via matrix multiplication units, thus
Externí odkaz:
http://arxiv.org/abs/2410.12614
Autor:
Berman, Edward, Ginesin, Jacob
Julia has been heralded as a potential successor to Python for scientific machine learning and numerical computing, boasting ergonomic and performance improvements. Since Julia's inception in 2012 and declaration of language goals in 2017, its ecosys
Externí odkaz:
http://arxiv.org/abs/2410.10908
Computed Tomography (CT) reconstruction of objects with cylindrical symmetry can be performed with a single projection. When the measured rays are parallel, and the axis of symmetry is perpendicular to the optical axis, the data can be modeled with t
Externí odkaz:
http://arxiv.org/abs/2410.09837
This contribution shows how a-posteriori error estimators based on equilibrated fluxes - H(div) functions fulfilling the underlying conservation law - can be implemented in FEniCSx. Therefore, dolfinx_eqlb is introduced, its algorithmic structure is
Externí odkaz:
http://arxiv.org/abs/2410.09764
Autor:
Cui, Cu, Kanschat, Guido
This paper presents a matrix-free multigrid method for solving the Stokes problem, discretized using $H^{\text{div}}$-conforming discontinuous Galerkin methods. We employ a Schur complement method combined with the fast diagonalization method for the
Externí odkaz:
http://arxiv.org/abs/2410.09497
Federated Learning (FL) is an emerging paradigm that enables intelligent agents to collaboratively train Machine Learning (ML) models in a distributed manner, eliminating the need for sharing their local data. The recent work (arXiv:2106.02969) intro
Externí odkaz:
http://arxiv.org/abs/2410.08760
Autor:
Hörnblad, Niklas
In the world of linear algebra computation, a well-established standard exists called BLAS(Basic Linear Algebra Subprograms). This standard has been crucial for the development of software using linear algebra operations. Its benefits include portabi
Externí odkaz:
http://arxiv.org/abs/2410.06770
Computed Tomography (CT) is an essential non-destructive three dimensional imaging modality used in medicine, security screening, and inspection of manufactured components. Typical CT data acquisition entails the collection of a thousand or more proj
Externí odkaz:
http://arxiv.org/abs/2410.07552
Autor:
Yadrov, Artem, Panchekha, Pavel
Evaluating a real-valued expression to high precision is a key building block in computational mathematics, physics, and numerics. A typical implementation uses a uniform precision for each operation, and doubles that precision until the real result
Externí odkaz:
http://arxiv.org/abs/2410.07468