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Applied Mathematics Research for Exascale Computing
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Moving-least-squares-particle hydrodynamics?I. Consistency and stability
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Increasing Memory Locality by Executing Several Model Instances Simultaneously
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On the convergence of a relaxation method with natural constraints on the elliptic operator
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A multirate time integrator for regularized Stokeslets
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Stochastic finite element methods for partial differential equations with random input data
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Spectral Deferred Correction Methods for Ordinary Differential Equations
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Multi-Level Adaptive Solutions to Boundary-Value Problems
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Algorithm-Based Fault Tolerance for Matrix Operations
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Feature-Based Statistical Analysis of Combustion Simulation Data
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The Isomap Algorithm and Topological Stability
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High-Order Collocation Methods for Differential Equations with Random Inputs
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An Anisotropic Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data
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The Convergence Theory of Particle-In-Cell Methods for Multidimensional Vlasov–Poisson Systems
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Galerkin Finite Element Approximations of Stochastic Elliptic Partial Differential Equations
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Exponential Integrators for Large Systems of Differential Equations
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Toward resilient algorithms and applications
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Parallel methods for integrating ordinary differential equations
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Design and Analysis of Computer Experiments
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Applied Mathematics at the U.S. Department of Energy: Past, Present and a View to the Future
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Predictive Capability Maturity Model for computational modeling and simulation.
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Semi-implicit spectral deferred correction methods for ordinary differential equations
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Route to exascale: Novel mathematical methods, scalable algorithms and Computational Science skills
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Stochastic finite element methods for partial differential equations with random input data
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Empirical investigation: performance and power‐consumption based dual‐level model for exascale computing systems
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