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 2603.05366cs.DC
收藏

大规模辐射流体动力学:使用FleCSI比较MPI和异步多任务运行时

Radiation Hydrodynamics at Scale: Comparing MPI and Asynchronous Many-Task Runtimes with FleCSI

University of Stuttgart(斯图加特大学);Louisiana State University(路易斯安那州立大学)

Alexander Strack, Hartmut Kaiser, Dirk Pflüger

AI总结:

本文通过FleCSI框架比较MPI与异步多任务运行时在大规模辐射流体动力学计算中的性能,发现HPX后端在部分场景下表现更优。

摘要:

编写高效的分布式代码仍然是一个劳动密集且复杂的任务。为了简化应用开发,Flexible Computational Science Infrastructure(FleCSI)框架提供了一个面向用户的、高级的编程接口,其基于任务型运行时模型构建。内部,FleCSI集成了最先进的并行化后端,包括MPI和异步多任务运行时(AMTRs)Legion和HPX,使应用程序能够充分利用异步并行性。在本工作中,我们使用FleCSI的三个后端对两个应用进行了基准测试,测试了多达1024个节点,旨在量化AMTR后端带来的优势和开销。作为代表应用,我们选择了一个简单的泊松求解器和多维辐射流体动力学代码HARD。在以通信为主的泊松求解器基准测试中,FleCSI在弱标度下使用MPI后端在多达131072个核心上实现了超过97%的并行效率,表明其抽象层仅引入了极小的开销。虽然Legion后端表现出明显的开销和标度限制,但HPX后端的开销与MPI+Kokkos相比仅略高。然而,HPX后端的标度性目前受到非优化的HPX集体操作的限制。在以计算为主的辐射流体动力学基准测试中,MPI和HPX后端之间的性能差距缩小。在少于64个节点的情况下,HPX后端优于MPI+Kokkos,弱标度下平均加速率为1.31,强标度下最高可达1.27。在仅流体动力学的HARD基准测试中,HPX后端在少于32个节点时表现更优,相对于MPI的加速率最高可达1.20,相对于MPI+Kokkos的加速率最高可达1.64。

英文摘要:

Writing efficient distributed code remains a labor-intensive and complex endeavor. To simplify application development, the Flexible Computational Science Infrastructure (FleCSI) framework offers a user-oriented, high-level programming interface that is built upon a task-based runtime model. Internally, FleCSI integrates state-of-the-art parallelization backends, including MPI and the asynchronous many-task runtimes (AMTRs) Legion and HPX, enabling applications to fully leverage asynchronous parallelism. In this work, we benchmark two applications using FleCSI's three backends on up to 1024 nodes, intending to quantify the advantages and overheads introduced by the AMTR backends. As representative applications, we select a simple Poisson solver and the multidimensional radiation hydrodynamics code HARD. In the communication-focused Poisson solver benchmark, FleCSI achieves over 97% parallel efficiency using the MPI backend under weak scaling on up to 131072 cores, indicating that only minimal overhead is introduced by its abstraction layer. While the Legion backend exhibits notable overheads and scaling limitations, the HPX backend introduces only marginal overhead compared to MPI+Kokkos. However, the scalability of the HPX backend is currently limited due to the usage of non-optimized HPX collective operations. In the computation-focused radiation hydrodynamics benchmarks, the performance gap between the MPI and HPX backends fades. On fewer than 64 nodes, the HPX backend outperforms MPI+Kokkos, achieving an average speedup of 1.31 under weak scaling and up to 1.27 under strong scaling. For the hydrodynamics-only HARD benchmark, the HPX backend demonstrates superior performance on fewer than 32 nodes, achieving speedups of up to 1.20 relative to MPI and up to 1.64 relative to MPI+Kokkos.

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。

↑