Anne Reinarz

Anne Reinarz
Durham University | DU · Department of Computer Science

PhD in Mathematics

About

26
Publications
3,003
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164
Citations
Citations since 2016
25 Research Items
161 Citations
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201620172018201920202021202201020304050
201620172018201920202021202201020304050
201620172018201920202021202201020304050

Publications

Publications (26)
Preprint
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Resilient algorithms in high-performance computing are subject to rigorous non-functional constraints. Resiliency must not increase the runtime, memory footprint or I/O demands too significantly. We propose a task-based soft error detection scheme that relies on error criteria per task outcome. They formalise how ``dubious'' an outcome is, i.e. how...
Preprint
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Numerical models of complex real-world phenomena often necessitate High Performance Computing (HPC). Uncertainties increase problem dimensionality further and pose even greater challenges. We present a parallelization strategy for multilevel Markov chain Monte Carlo, a state-of-the-art, algorithmically scalable Uncertainty Quantification (UQ) algor...
Preprint
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We present a sequence of optimizations to the performance-critical compute kernels of the high-order discontinuous Galerkin solver of the hyperbolic PDE engine ExaHyPE -- successively tackling bottlenecks due to SIMD operations, cache hierarchies and restrictions in the software design. Starting from a generic scalar implementation of the numerical...
Chapter
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The development of a high performance PDE solver requires the combined expertise of interdisciplinary teams with respect to application domain, numerical scheme and low-level optimization. In this paper, we present how the ExaHyPE engine facilitates the collaboration of such teams by isolating three roles: application, algorithms, and optimization...
Chapter
We present an efficient implementation of the highly robust and scalable GenEO (Generalized Eigenproblems in the Overlap) preconditioner [16] in the high-performance PDE framework DUNE [6]. The GenEO coarse space is constructed by combining low energy solutions of a local generalised eigenproblem using a partition of unity. The main contribution of...
Article
Full-text available
ExaHyPE (“An Exascale Hyperbolic PDE Engine”) is a software engine for solving systems of first-order hyperbolic partial differential equations (PDEs). Hyperbolic PDEs are typically derived from the conservation laws of physics and are useful in a wide range of application areas. Applications powered by ExaHyPE can be run on a student’s laptop, but...
Preprint
Full-text available
The development of a high performance PDE solver requires the combined expertise of interdisciplinary teams w.r.t. application domain, numerical scheme and low-level optimization. In this paper, we present how the ExaHyPE engine facilitates the collaboration of such teams by isolating three roles -- application, algorithms, and optimization expert...
Article
Full-text available
In this paper we propose an extension of the generalized Lagrangian multiplier method (GLM) of Munz et al. [52], [30], which was originally conceived for the numerical solution of the Maxwell and MHD equations with divergence-type involutions, to the case of hyperbolic PDE systems with curl-type involutions. The key idea here is to solve an augment...
Article
Full-text available
The key innovation in this paper is an open-source, high-performance iterative solver for high contrast, strongly anisotropic elliptic partial differential equations implemented within dune-pdelab. The iterative solver exploits a robust, scalable two-level additive Schwarz preconditioner, GenEO (Spillane et al., 2014). The development of this solve...
Preprint
Full-text available
In this paper we propose an extension of the generalized Lagrangian multiplier method (GLM) of Munz et al. (JCP 2000, JCP 2002), which was originally conceived for the numerical solution of the Maxwell and MHD equations with divergence-type involutions, to the case of hyperbolic PDE systems with curl-type involutions. In particular, we apply the ne...
Article
The aim of this paper is to develop and analyse stable and accurate numerical approximation schemes for boundary integral formulations of the heat equation with Dirichlet boundary conditions. The accuracy of Galerkin discretisations for the resulting boundary integral formulations strongly depends on the choice of discretisation space. We develop a...
Preprint
Full-text available
We present an efficient implementation of the highly robust and scalable GenEO preconditioner in the high-performance PDE framework DUNE. The GenEO coarse space is constructed by combining low energy solutions of a local generalised eigenproblem using a partition of unity. In this paper we demonstrate both weak and strong scaling for the GenEO solv...
Preprint
Full-text available
ExaHyPE ("An Exascale Hyperbolic PDE Engine") is a software engine for solving systems of first-order hyperbolic partial differential equations (PDEs). Hyperbolic PDEs are typically derived from the conservation laws of physics and are useful in a wide range of application areas. Applications powered by ExaHyPE can be run on a student's laptop, but...
Preprint
Full-text available
ExaHyPE (``An Exascale Hyperbolic PDE Engine'') is a software engine for solving systems of first-order hyperbolic partial differential equations (PDEs). Hyperbolic PDEs are typically derived from the conservation laws of physics and are useful in a wide range of application areas. Applications powered by ExaHyPE can be run on a student's laptop, b...
Preprint
Full-text available
dune-composites is the first open-source software framework designed to support the development of high-performance scalable solvers for composite applications. dune-composite is an initiative to overcome the limitations of commercially available solvers by encapsulating the mathematical complexities of the underlying solvers within an efficient C+...
Preprint
Soft error rates are increasing as modern architectures require increasingly small features at low voltages. Due to the large number of components used in HPC architectures, these are particularly vulnerable to soft errors. Hence, when designing applications that run for long time periods on large machines, algorithmic resilience must be taken into...
Article
Full-text available
This paper presents a novel stochastic framework to quantify the knock down in strength from out-of-plane wrinkles at the coupon level. The key innovation is a Markov Chain Monte Carlo algorithm which rigorously derives the stochastic distribution of wrinkle defects directly informed from image data of defects. The approach significantly reduces un...
Preprint
Full-text available
The aim of this paper is to develop stable and accurate numerical schemes for boundary integral formulations of the heat equation with Dirichlet boundary conditions. The accuracy of Galerkin discretisations for the resulting boundary integral formulations depends mainly on the choice of discretisation space. We develop a-priori error analysis utili...
Preprint
Full-text available
This paper presents a novel stochastic framework to quantify the knock down in strength from out-of-plane wrinkles at the coupon level. The key innovation is a Markov Chain Monte Carlo algorithm which rigorously derives the stochastic distribution of wrinkle defects directly informed from image data of defects. The approach significantly reduces un...
Article
Full-text available
Finite element (FE) analysis has the potential to offset much of the expensive experimental testing currently required to certify aerospace laminates. However, large numbers of degrees of freedom are necessary to model entire aircraft components whilst accurately resolving micro-scale defects. The new module dune-composites, implemented within DUNE...
Article
Full-text available
We introduce and analyze a family of algorithms for an efficient numerical approximation of integrals of the form I=@!"C"^"("^"1"^")@!"C"^"("^"2"^")F(x,y,y-x)dydx where C^(^1^), C^(^2^) are d-dimensional parallelotopes (i.e. affine images of d-hypercubes) and F has a singularity at y-x=0. Such integrals appear in Galerkin discretization of integral...

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