Zobrazeno 1 - 10
of 89
pro vyhledávání: '"ZAMPINI, STEFANO"'
Autor:
Mills, Richard Tran, Adams, Mark, Balay, Satish, Brown, Jed, Faibussowitsch, Jacob, Isaac, Toby, Knepley, Matthew, Munson, Todd, Suh, Hansol, Zampini, Stefano, Zhang, Hong, Zhang, Junchao
The Portable Extensible Toolkit for Scientific Computation (PETSc) library provides scalable solvers for nonlinear time-dependent differential and algebraic equations and for numerical optimization via the Toolkit for Advanced Optimization (TAO). PET
Externí odkaz:
http://arxiv.org/abs/2406.08646
In recent years, we have witnessed the emergence of scientific machine learning as a data-driven tool for the analysis, by means of deep-learning techniques, of data produced by computational science and engineering applications. At the core of these
Externí odkaz:
http://arxiv.org/abs/2403.12188
Leveraging Graphics Processing Units (GPUs) to accelerate scientific software has proven to be highly successful, but in order to extract more performance, GPU programmers must overcome the high latency costs associated with their use. One method of
Externí odkaz:
http://arxiv.org/abs/2306.17801
The Virtual Element Method (VEM) is a novel family of numerical methods for approximating partial differential equations on very general polygonal or polyhedral computational grids. This work aims to propose a Balancing Domain Decomposition by Constr
Externí odkaz:
http://arxiv.org/abs/2304.09770
Hierarchical $\mathcal{H}^2$-matrices are asymptotically optimal representations for the discretizations of non-local operators such as those arising in integral equations or from kernel functions. Their $O(N)$ complexity in both memory and operator
Externí odkaz:
http://arxiv.org/abs/2109.05451
Tile low rank representations of dense matrices partition them into blocks of roughly uniform size, where each off-diagonal tile is compressed and stored as its own low rank factorization. They offer an attractive representation for many data-sparse
Externí odkaz:
http://arxiv.org/abs/2108.11932
Autor:
Zhang, Junchao, Brown, Jed, Balay, Satish, Faibussowitsch, Jacob, Knepley, Matthew, Marin, Oana, Mills, Richard Tran, Munson, Todd, Smith, Barry F., Zampini, Stefano
PetscSF, the communication component of the Portable, Extensible Toolkit for Scientific Computation (PETSc), is designed to provide PETSc's communication infrastructure suitable for exascale computers that utilize GPUs and other accelerators. PetscSF
Externí odkaz:
http://arxiv.org/abs/2102.13018
Autor:
Mills, Richard Tran, Adams, Mark F., Balay, Satish, Brown, Jed, Dener, Alp, Knepley, Matthew, Kruger, Scott E., Morgan, Hannah, Munson, Todd, Rupp, Karl, Smith, Barry F., Zampini, Stefano, Zhang, Hong, Zhang, Junchao
The Portable Extensible Toolkit for Scientific computation (PETSc) library delivers scalable solvers for nonlinear time-dependent differential and algebraic equations and for numerical optimization.The PETSc design for performance portability address
Externí odkaz:
http://arxiv.org/abs/2011.00715
Autor:
Ambartsumyan, Ilona, Boukaram, Wajih, Bui-Thanh, Tan, Ghattas, Omar, Keyes, David, Stadler, Georg, Turkiyyah, George, Zampini, Stefano
Hessian operators arising in inverse problems governed by partial differential equations (PDEs) play a critical role in delivering efficient, dimension-independent convergence for both Newton solution of deterministic inverse problems, as well as Mar
Externí odkaz:
http://arxiv.org/abs/2003.10173