2,407 research outputs found
Construction and Application of an AMR Algorithm for Distributed Memory Computers
While the parallelization of blockstructured adaptive mesh refinement techniques is relatively straight-forward on shared memory architectures, appropriate distribution strategies for the emerging generation of distributed
memory machines are a topic of on-going research. In this paper, a locality-preserving domain decomposition is proposed that partitions the entire AMR hierarchy from the base level on. It is shown that the approach reduces the
communication costs and simplifies the implementation. Emphasis is put on the effective parallelization of the flux correction procedure at coarse-fine boundaries, which is indispensable for conservative finite volume schemes. An
easily reproducible standard benchmark and a highly resolved parallel AMR
simulation of a diffracting hydrogen-oxygen detonation demonstrate the proposed
strategy in practice
Optimisation of patch distribution strategies for AMR applications
As core counts increase in the world's most powerful supercomputers, applications are becoming limited not only by computational power, but also by data availability. In the race to exascale, efficient and effective communication policies are key to achieving optimal application performance. Applications using adaptive mesh refinement (AMR) trade off communication for computational load balancing, to enable the focused computation of specific areas of interest. This class of application is particularly susceptible to the communication performance of the underlying architectures, and are inherently difficult to scale efficiently. In this paper we present a study of the effect of patch distribution strategies on the scalability of an AMR code. We demonstrate the significance of patch placement on communication overheads, and by balancing the computation and communication costs of patches, we develop a scheme to optimise performance of a specific, industry-strength, benchmark application
Performance and Optimization Abstractions for Large Scale Heterogeneous Systems in the Cactus/Chemora Framework
We describe a set of lower-level abstractions to improve performance on
modern large scale heterogeneous systems. These provide portable access to
system- and hardware-dependent features, automatically apply dynamic
optimizations at run time, and target stencil-based codes used in finite
differencing, finite volume, or block-structured adaptive mesh refinement
codes.
These abstractions include a novel data structure to manage refinement
information for block-structured adaptive mesh refinement, an iterator
mechanism to efficiently traverse multi-dimensional arrays in stencil-based
codes, and a portable API and implementation for explicit SIMD vectorization.
These abstractions can either be employed manually, or be targeted by
automated code generation, or be used via support libraries by compilers during
code generation. The implementations described below are available in the
Cactus framework, and are used e.g. in the Einstein Toolkit for relativistic
astrophysics simulations
Achieving Extreme Resolution in Numerical Cosmology Using Adaptive Mesh Refinement: Resolving Primordial Star Formation
As an entry for the 2001 Gordon Bell Award in the "special" category, we
describe our 3-d, hybrid, adaptive mesh refinement (AMR) code, Enzo, designed
for high-resolution, multiphysics, cosmological structure formation
simulations. Our parallel implementation places no limit on the depth or
complexity of the adaptive grid hierarchy, allowing us to achieve unprecedented
spatial and temporal dynamic range. We report on a simulation of primordial
star formation which develops over 8000 subgrids at 34 levels of refinement to
achieve a local refinement of a factor of 10^12 in space and time. This allows
us to resolve the properties of the first stars which form in the universe
assuming standard physics and a standard cosmological model. Achieving extreme
resolution requires the use of 128-bit extended precision arithmetic (EPA) to
accurately specify the subgrid positions. We describe our EPA AMR
implementation on the IBM SP2 Blue Horizon system at the San Diego
Supercomputer Center.Comment: 23 pages, 5 figures. Peer reviewed technical paper accepted to the
proceedings of Supercomputing 2001. This entry was a Gordon Bell Prize
finalist. For more information visit http://www.TomAbel.com/GB
AMRA: An Adaptive Mesh Refinement Hydrodynamic Code for Astrophysics
Implementation details and test cases of a newly developed hydrodynamic code,
AMRA, are presented. The numerical scheme exploits the adaptive mesh refinement
technique coupled to modern high-resolution schemes which are suitable for
relativistic and non-relativistic flows. Various physical processes are
incorporated using the operator splitting approach, and include self-gravity,
nuclear burning, physical viscosity, implicit and explicit schemes for
conductive transport, simplified photoionization, and radiative losses from an
optically thin plasma. Several aspects related to the accuracy and stability of
the scheme are discussed in the context of hydrodynamic and astrophysical
flows.Comment: 41 pages, 21 figures (9 low-resolution), LaTeX, requires elsart.cls,
submitted to Comp. Phys. Comm.; additional documentation and high-resolution
figures available from http://www.camk.edu.pl/~tomek/AMRA/index.htm
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