arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 1807.06128gr-qcastro-ph.HE
收藏

中等质量比双星黑洞吸气的大规模并行模拟

Massively Parallel Simulations of Binary Black Hole Intermediate-Mass-Ratio Inspirals

Milinda Fernando, David Neilsen, Hyun Lim, Eric Hirschmann, Hari Sundar

摘要:

我们提出了一个高度可扩展的框架,目标感兴趣的数值相对论和更广泛的天体物理学社区的问题。该框架结合了并行八叉树细化自适应网格与小波自适应多分辨率和物理模块来求解BSSN公式中的广义相对论爱因斯坦方程。这项工作的目标是进行先进的,大规模并行数值模拟的中间质量比的灵感(IMRIs)的质量比为100:1的顺序的二元黑洞。这些研究将用于生成LIGO数据分析中使用的波形,并校准半解析近似方法。我们的框架包括一个分布式内存八叉树为基础的自适应网格框架结合节点本地代码生成器。代码生成器使我们的代码可以跨不同的架构移植。对应于目标应用程序的方程以符号表示法编写,并且可以独立于应用程序添加用于不同架构的生成器。此外,这种符号接口也使我们的代码可扩展,因此已被设计为很容易地适应许多现有的算法在天体物理学等离子体动力学和辐射流体力学。我们的自适应网格化算法和数据结构已被优化为现代体系结构与深内存层次。这使我们的框架能够在现代领导架构上实现出色的性能和可扩展性。我们表现出良好的弱可扩展性高达131K内核的ORNL的泰坦二进制合并质量比高达100。

英文摘要:

We present a highly-scalable framework that targets problems of interest to the numerical relativity and broader astrophysics communities. This framework combines a parallel octree-refined adaptive mesh with a wavelet adaptive multiresolution and a physics module to solve the Einstein equations of general relativity in the BSSN formulation. The goal of this work is to perform advanced, massively parallel numerical simulations of Intermediate Mass Ratio Inspirals (IMRIs) of binary black holes with mass ratios on the order of 100:1. These studies will be used to generate waveforms as used in LIGO data analysis and to calibrate semi-analytical approximate methods. Our framework consists of a distributed memory octree-based adaptive meshing framework in conjunction with a node-local code generator. The code generator makes our code portable across different architectures. The equations corresponding to the target application are written in symbolic notation and generators for different architectures can be added independent of the application. Additionally, this symbolic interface also makes our code extensible, and as such has been designed to easily accommodate many existing algorithms in astrophysics for plasma dynamics and radiation hydrodynamics. Our adaptive meshing algorithms and data-structures have been optimized for modern architectures with deep memory hierarchies. This enables our framework to have achieve excellent performance and scalability on modern leadership architectures. We demonstrate excellent weak scalability up to 131K cores on ORNL's Titan for binary mergers for mass ratios up to 100.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑