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Dive into the research topics where Carsten Burstedde is active.

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Featured researches published by Carsten Burstedde.


Physica A-statistical Mechanics and Its Applications | 2001

Simulation of pedestrian dynamics using a two-dimensional cellular automaton

Carsten Burstedde; Kai Klauck; Andreas Schadschneider; J. Zittartz

We propose a two-dimensional cellular automaton model to simulate pedestrian traffic. It is a vmax=1 model with exclusion statistics and parallel dynamics. Long-range interactions between the pedestrians are mediated by a so-called floor field which modifies the transition rates to neighbouring cells. This field, which can be discrete or continuous, is subject to diffusion and decay. Furthermore it can be modified by the motion of the pedestrians. Therefore, the model uses an idea similar to chemotaxis, but with pedestrians following a virtual rather than a chemical trace. Our main goal is to show that the introduction of such a floor field is sufficient to model collective effects and self-organization encountered in pedestrian dynamics, e.g. lane formation in counterflow through a large corridor. As an application we also present simulations of the evacuation of a large room with reduced visibility, e.g. due to failure of lights or smoke.


SIAM Journal on Scientific Computing | 2011

p4est : Scalable Algorithms for Parallel Adaptive Mesh Refinement on Forests of Octrees

Carsten Burstedde; Lucas C. Wilcox; Omar Ghattas

We present scalable algorithms for parallel adaptive mesh refinement and coarsening (AMR), partitioning, and 2:1 balancing on computational domains composed of multiple connected two-dimensional quadtrees or three-dimensional octrees, referred to as a forest of octrees. By distributing the union of octants from all octrees in parallel, we combine the high scalability proven previously for adaptive single-octree algorithms with the geometric flexibility that can be achieved by arbitrarily connected hexahedral macromeshes, in which each macroelement is the root of an adapted octree. A key concept of our approach is an encoding scheme of the interoctree connectivity that permits arbitrary relative orientations between octrees. Based on this encoding we develop interoctree transformations of octants. These form the basis for high-level parallel octree algorithms, which are designed to interact with an application code such as a numerical solver for partial differential equations. We have implemented and tested these algorithms in the p4est software library. We demonstrate the parallel scalability of p4est on its own and in combination with two geophysics codes. Using p4est we generate and adapt multioctree meshes with up to


Science | 2010

The Dynamics of Plate Tectonics and Mantle Flow: From Local to Global Scales

Georg Stadler; Michael Gurnis; Carsten Burstedde; Lucas C. Wilcox; Laura Alisic; Omar Ghattas

5.13times10^{11}


SIAM Journal on Scientific Computing | 2012

A Stochastic Newton MCMC Method for Large-Scale Statistical Inverse Problems with Application to Seismic Inversion

James F. Martin; Lucas C. Wilcox; Carsten Burstedde; Omar Ghattas

octants on as many as 220,320 CPU cores and execute the 2:1 balance algorithm in less than 10 seconds per million octants per process.


Journal of Computational Physics | 2010

A high-order discontinuous Galerkin method for wave propagation through coupled elastic-acoustic media

Lucas C. Wilcox; Georg Stadler; Carsten Burstedde; Omar Ghattas

Improving Earth Models The geophysical processes responsible for shaping the planets surface and interior need largescale simulations, but to achieve high resolution at these scales is costly and tends to focus on gradual processes such as plate tectonics. By using large parallel supercomputers, Stadler et al. (p. 1033; see the Perspective by Becker; see the cover) have improved on a commonly used method—adaptive mesh refinement—to increase the resolution of global geodynamic models to the scale of a single kilometer and been able to reveal unexpected insights into localized processes, such as subduction zone mechanics, thermal anomalies in the lower mantle, and the speed of movement of oceanic plates. Computational advances enable the modeling of global geophysical processes to the scale of a kilometer. Plate tectonics is regulated by driving and resisting forces concentrated at plate boundaries, but observationally constrained high-resolution models of global mantle flow remain a computational challenge. We capitalized on advances in adaptive mesh refinement algorithms on parallel computers to simulate global mantle flow by incorporating plate motions, with individual plate margins resolved down to a scale of 1 kilometer. Back-arc extension and slab rollback are emergent consequences of slab descent in the upper mantle. Cold thermal anomalies within the lower mantle couple into oceanic plates through narrow high-viscosity slabs, altering the velocity of oceanic plates. Viscous dissipation within the bending lithosphere at trenches amounts to ~5 to 20% of the total dissipation through the entire lithosphere and mantle.


ieee international conference on high performance computing data and analytics | 2008

Scalable adaptive mantle convection simulation on petascale supercomputers

Carsten Burstedde; Omar Ghattas; Michael Gurnis; Georg Stadler; Eh Tan; Tiankai Tu; Lucas C. Wilcox; Shijie Zhong

We address the solution of large-scale statistical inverse problems in the framework of Bayesian inference. The Markov chain Monte Carlo (MCMC) method is the most popular approach for sampling the posterior probability distribution that describes the solution of the statistical inverse problem. MCMC methods face two central difficulties when applied to large-scale inverse problems: first, the forward models (typically in the form of partial differential equations) that map uncertain parameters to observable quantities make the evaluation of the probability density at any point in parameter space very expensive; and second, the high-dimensional parameter spaces that arise upon discretization of infinite-dimensional parameter fields make the exploration of the probability density function prohibitive. The challenge for MCMC methods is to construct proposal functions that simultaneously provide a good approximation of the target density while being inexpensive to manipulate. Here we present a so-called Stoch...


ACM Transactions on Mathematical Software | 2011

Algorithms and data structures for massively parallel generic adaptive finite element codes

Wolfgang Bangerth; Carsten Burstedde; Timo Heister; Martin Kronbichler

We introduce a high-order discontinuous Galerkin (dG) scheme for the numerical solution of three-dimensional (3D) wave propagation problems in coupled elastic-acoustic media. A velocity-strain formulation is used, which allows for the solution of the acoustic and elastic wave equations within the same unified framework. Careful attention is directed at the derivation of a numerical flux that preserves high-order accuracy in the presence of material discontinuities, including elastic-acoustic interfaces. Explicit expressions for the 3D upwind numerical flux, derived as an exact solution for the relevant Riemann problem, are provided. The method supports h-non-conforming meshes, which are particularly effective at allowing local adaptation of the mesh size to resolve strong contrasts in the local wavelength, as well as dynamic adaptivity to track solution features. The use of high-order elements controls numerical dispersion, enabling propagation over many wave periods. We prove consistency and stability of the proposed dG scheme. To study the numerical accuracy and convergence of the proposed method, we compare against analytical solutions for wave propagation problems with interfaces, including Rayleigh, Lamb, Scholte, and Stoneley waves as well as plane waves impinging on an elastic-acoustic interface. Spectral rates of convergence are demonstrated for these problems, which include a non-conforming mesh case. Finally, we present scalability results for a parallel implementation of the proposed high-order dG scheme for large-scale seismic wave propagation in a simplified earth model, demonstrating high parallel efficiency for strong scaling to the full size of the Jaguar Cray XT5 supercomputer.


ieee international conference on high performance computing data and analytics | 2010

Extreme-Scale AMR

Carsten Burstedde; Omar Ghattas; Michael Gurnis; Tobin Isaac; Georg Stadler; Tim Warburton; Lucas C. Wilcox

Mantle convection is the principal control on the thermal and geological evolution of the Earth. Mantle convection modeling involves solution of the mass, momentum, and energy equations for a viscous, creeping, incompressible non-Newtonian fluid at high Rayleigh and Peclet numbers. Our goal is to conduct global mantle convection simulations that can resolve faulted plate boundaries, down to 1 km scales. However, uniform resolution at these scales would result in meshes with a trillion elements, which would elude even sustained petaflops supercomputers. Thus parallel adaptive mesh refinement and coarsening (AMR) is essential. We present RHEA, a new generation mantle convection code designed to scale to hundreds of thousands of cores. RHEA is built on ALPS, a parallel octree-based adaptive mesh finite element library that provides new distributed data structures and parallel algorithms for dynamic coarsening, refinement, rebalancing, and repartitioning of the mesh. ALPS currently supports low order continuous Lagrange elements, and arbitrary order discontinuous Galerkin spectral elements, on octree meshes. A forest-of-octrees implementation permits nearly arbitrary geometries to be accommodated. Using TACCs 579 teraflops Ranger supercomputer, we demonstrate excellent weak and strong scalability of parallel AMR on up to 62,464 cores for problems with up to 12.4 billion elements. With RHEAS adaptive capabilities, we have been able to reduce the number of elements by over three orders of magnitude, thus enabling us to simulate large-scale mantle convection with finest local resolution of 1.5 km.


Journal of Geophysical Research | 2012

Multi-scale dynamics and rheology of mantle flow with plates

Laura Alisic; Michael Gurnis; Georg Stadler; Carsten Burstedde; Omar Ghattas

Todays largest supercomputers have 100,000s of processor cores and offer the potential to solve partial differential equations discretized by billions of unknowns. However, the complexity of scaling to such large machines and problem sizes has so far prevented the emergence of generic software libraries that support such computations, although these would lower the threshold of entry and enable many more applications to benefit from large-scale computing.n We are concerned with providing this functionality for mesh-adaptive finite element computations. We assume the existence of an “oracle” that implements the generation and modification of an adaptive mesh distributed across many processors, and that responds to queries about its structure. Based on querying the oracle, we develop scalable algorithms and data structures for generic finite element methods. Specifically, we consider the parallel distribution of mesh data, global enumeration of degrees of freedom, constraints, and postprocessing. Our algorithms remove the bottlenecks that typically limit large-scale adaptive finite element analyses.n We demonstrate scalability of complete finite element workflows on up to 16,384 processors. An implementation of the proposed algorithms, based on the open source software p4est as mesh oracle, is provided under an open source license through the widely used deal.II finite element software library.


Geophysics | 2009

Algorithmic strategies for full waveform inversion: 1D experiments

Carsten Burstedde; Omar Ghattas

Many problems are characterized by dynamics occurring on a wide range of length and time scales. One approach to overcoming the tyranny of scales is adaptive mesh refinement/coarsening (AMR), which dynamically adapts the mesh to resolve features of interest. However, the benefits of AMR are difficult to achieve in practice, particularly on the petascale computers that are essential for difficult problems. Due to the complex dynamic data structures and frequent load balancing, scaling dynamic AMR to hundreds of thousands of cores has long been considered a challenge. Another difficulty is extending parallel AMR techniques to high-order-accurate, complex-geometry-respecting methods that are favored for many classes of problems. Here we present new parallel algorithms for parallel dynamic AMR on forest-ofoctrees geometries with arbitrary-order continuous and discontinuous finite/spectral element discretizations. The implementations of these algorithms exhibit excellent weak and strong scaling to over 224,000 Cray XT5 cores for multiscale geophysics problems.

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Omar Ghattas

University of Texas at Austin

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Georg Stadler

Courant Institute of Mathematical Sciences

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Lucas C. Wilcox

Naval Postgraduate School

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Michael Gurnis

California Institute of Technology

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Laura Alisic

California Institute of Technology

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Tiankai Tu

Carnegie Mellon University

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Tobin Isaac

Georgia Institute of Technology

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Eh Tan

California Institute of Technology

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Shijie Zhong

University of Colorado Boulder

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