Zobrazeno 1 - 10
of 10 059
pro vyhledávání: '"Cu, A."'
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
Autor:
Wu, Xianhu, Bi, Jieyu, Cu, Guanglei, Liu, Nian, Xia, Gaojie, Sun, Jilong, Jiang, Jiaxin, Lu, Ning, Li, Ping, Zhao, Chunyi, Zuo, Zewen, Gu, Min
The buried interface between the electron transport layer and the perovskite layer suffers from severe interface defects and imperfect energy level alignment. To address this issue, this study employs a multifunctional organic molecule, curcumin, to
Externí odkaz:
http://arxiv.org/abs/2408.17167
Autor:
Cui, Cu
In this paper, we explore the acceleration of tensor product operations in finite element methods, leveraging the computational power of the NVIDIA A100 GPU Tensor Cores. We provide an accessible overview of the necessary mathematical background and
Externí odkaz:
http://arxiv.org/abs/2407.09621
We present a GPU implementation of vertex-patch smoothers for higher order finite element methods in two and three dimensions. Analysis shows that they are not memory bound with respect to GPU DRAM, but with respect to on-chip scratchpad memory. Mult
Externí odkaz:
http://arxiv.org/abs/2405.19004
Autor:
Cui, Cu, Kanschat, Guido
We present a matrix-free multigrid method for high-order discontinuous Galerkin (DG) finite element methods with GPU acceleration. A performance analysis is conducted, comparing various data and compute layouts. Smoother implementations are optimized
Externí odkaz:
http://arxiv.org/abs/2405.18982
A symmetry-preserving truncation of the quantum field equations describing hadron properties is used to deliver parameter-free predictions for all nucleon elastic electromagnetic form factors and their flavour separation to large values of momentum t
Externí odkaz:
http://arxiv.org/abs/2403.08088
Autor:
Le, Xuan Cu
Publikováno v:
The International Journal of Logistics Management, 2024, Vol. 35, Issue 6, pp. 2012-2031.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJLM-10-2023-0426
Publikováno v:
BMC Medical Education, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background Understanding students’ career intentions through evidence-based approaches is crucial for developing effective career guidance and intervention strategies. Although there has been considerable attention in this field, research
Externí odkaz:
https://doaj.org/article/3968c9dd70ae4fdd935834d3139cfb2c
Autor:
Correll CU, Rubio JM, Citrome L, Mychaskiw MA, Thompson S, Franzenburg KR, Suett M, Kotak S, Kane JM
Publikováno v:
Neuropsychiatric Disease and Treatment, Vol Volume 20, Pp 1995-2010 (2024)
Christoph U Correll,1– 4,* Jose M Rubio,1– 3,* Leslie Citrome,5,* Marko A Mychaskiw,6 Stephen Thompson,6 Kelli R Franzenburg,7 Mark Suett,8 Sameer Kotak,9 John M Kane1– 3,* 1Department of Psychiatry, The Zucker Hillside Hospital
Externí odkaz:
https://doaj.org/article/959f61b128e348409830ac5b7602f26d
Publikováno v:
ICCV2023
Domain generalization (DG) seeks to learn robust models that generalize well under unknown distribution shifts. As a critical aspect of DG, optimizer selection has not been explored in depth. Currently, most DG methods follow the widely used benchmar
Externí odkaz:
http://arxiv.org/abs/2307.11108