38 citations · 195 across the 39 of their papers we have counts for
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Generalizing Reduction-Based Algebraic Multigrid
Tareq Zaman, Nicolas Nytko, Ali Taghibakhshi +3
Algebraic Multigrid (AMG) methods are often robust and effective solvers for solving the large and sparse linear systems that arise from discretized PDEs and other problems, relyin…
Optimized Sparse Matrix Operations for Reverse Mode Automatic Differentiation
Nicolas Nytko, Ali Taghibakhshi, Tareq Uz Zaman +3
Sparse matrix representations are ubiquitous in computational science and machine learning, leading to significant reductions in compute time, in comparison to dense representation…
Constraint-satisfying Krylov solvers for structure-preserving discretisations
James Jackaman, Scott MacLachlan
A key consideration in the development of numerical schemes for time-dependent partial differential equations (PDEs) is the ability to preserve certain properties of the continuum…
Multigrid reduction-in-time convergence for advection problems: A Fourier analysis perspective
H. De Sterck, S. Friedhoff, O. A. Krzysik +1
A long-standing issue in the parallel-in-time community is the poor convergence of standard iterative parallel-in-time methods for hyperbolic partial differential equations (PDEs),…
Finite-element discretization of the smectic density equation
Patrick E. Farrell, Abdalaziz Hamdan, Scott P. MacLachlan
The fourth-order PDE that models the density variation of smectic A liquid crystals presents unique challenges in its (numerical) analysis beyond more common fourth-order operators…
Learning Interface Conditions in Domain Decomposition Solvers
Ali Taghibakhshi, Nicolas Nytko, Tareq Zaman +3
Domain decomposition methods are widely used and effective in the approximation of solutions to partial differential equations. Yet the optimal construction of these methods requir…