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In situ and in-transit analysis of cosmological simulations

机译:宇宙模拟的原位和在途分析

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Modern cosmological simulations have reached the trillion-element scale, rendering data storage and subsequent analysis formidable tasks. To address this circumstance, we present a new MPI-parallel approach for analysis of simulation data while the simulation runs, as an alternative to the traditional workflow consisting of periodically saving large data sets to disk for subsequent ‘offline’ analysis. We demonstrate this approach in the compressible gasdynamics/ N -body code Nyx, a hybrid MPI + OpenMP $mbox{MPI}+mbox{OpenMP}$ code based on the BoxLib framework, used for large-scale cosmological simulations. We have enabled on-the-fly workflows in two different ways: one is a straightforward approach consisting of all MPI processes periodically halting the main simulation and analyzing each component of data that they own (‘ in situ ’). The other consists of partitioning processes into disjoint MPI groups, with one performing the simulation and periodically sending data to the other ‘sidecar’ group, which post-processes it while the simulation continues (‘in-transit’). The two groups execute their tasks asynchronously, stopping only to synchronize when a new set of simulation data needs to be analyzed. For both the in situ and in-transit approaches, we experiment with two different analysis suites with distinct performance behavior: one which finds dark matter halos in the simulation using merge trees to calculate the mass contained within iso-density contours, and another which calculates probability distribution functions and power spectra of various fields in the simulation. Both are common analysis tasks for cosmology, and both result in summary statistics significantly smaller than the original data set. We study the behavior of each type of analysis in each workflow in order to determine the optimal configuration for the different data analysis algorithms.
机译:现代宇宙学模拟已经达到了数万亿个元素的规模,从而提供了数据存储和后续分析的艰巨任务。为了解决这种情况,我们提出了一种新的MPI并行方法,用于在模拟运行时分析模拟数据,作为传统工作流的一种替代方法,该传统工作流包括定期将大数据集保存到磁盘以进行后续的“离线”分析。我们在可压缩气体动力学/ N体代码Nyx中演示了这种方法,Nyx是基于BoxLib框架的MPI + OpenMP $ mbox {MPI} + mbox {OpenMP} $混合代码,用于大规模宇宙模拟。我们以两种不同的方式启用了实时工作流程:一种是直接的方法,由所有MPI流程组成,该流程定期停止主要模拟并分析其拥有的数据的每个组成部分(“原位”)。另一个包括将流程划分为不相交的MPI组,一个组执行模拟,并定期将数据发送到另一个“ sidecar”组,后者在模拟继续进行时(“运输中”)对其进行后处理。两组异步执行任务,仅在需要分析一组新的仿真数据时才停止同步。对于现场方法和运输方法,我们都尝试了两种具有不同性能行为的不同分析套件:一种使用合并树在模拟中找到暗物质晕,以计算等密度轮廓中包含的质量,另一种计算模拟中各个场的概率分布函数和功率谱。两者都是宇宙学的常见分析任务,并且都导致汇总统计信息显着小于原始数据集。我们研究每种工作流中每种分析类型的行为,以便为不同的数据分析算法确定最佳配置。

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