Supernova Simulations with the Radiation Hydrodynamics Code PROMETHEUS/VERTEX

Müller, Bernhard; Marek, Andreas; Benkert, Katharina; Kifonidis, K.; Janka, Hans‐Thomas

doi:10.1007/978-3-540-74384-2_15

Cited by 1 publication

(2 citation statements)

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“…Therefore, the Max-Planck Institute for Astrophysics, Garching, Germany, currently uses in their code PROMETHEUS/VERTEX a 2D hydro model and a ''ray-by-ray-plus'' variable Eddington factor method, respectively. Successful explosions have already been obtained for some progenitor models in the [8][9][10][11][12][13][14][15] M range with this model as shown in Fig. 2.…”

Section: Introductionmentioning

confidence: 99%

“…However, the single CPU performance is limited due to the scalar architecture. On the other hand, Müller et al (2007) have shown that the code is well-suited for vector computers such as the NEC SX-8 installation at HLRS. Benkert and Fischer (2007) have recently optimized the kernel, the solution of the block-pentadiagonal linear system of equations, for this architecture.…”

Section: Introductionmentioning

confidence: 99%

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Reducing Turn-around Times for Supernova Simulations

Benkert

Müller

Resch

2009

IIS

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Many questions in the field of supernova core collapse still remain unanswered due to the complex multi-faceted nature of the problem. A direct computation of the full neutrino radiation hydrodynamics would require a sustained performance of PetaFlop/s and is therefore unfeasible on today's supercomputers. The modeling required to reduce the computational effort is accompanied by the ambiguity which physical effects are indispensable. As input parameters also contain a certain amount of uncertainty, parameter studies are necessary. For this reason, supernova simulations still require TFlop/s and a careful mapping of the software onto the given hardware is necessary to assure the maximum performance possible.In this paper, we describe the necessary extensions to the partly existing MPI parallelization of the simulation code PROMETHEUS/VERTEX from the Max-Planck Institute for Astrophysics in Garching. With a complete distributed memory parallelization, turn-around times can be decreased substantially. We show for a 15 solar mass model that an efficient usage of up to 32 nodes NEC SX-8 is possible and therefore turn-around times can be reduced by a factor of nearly seven.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%