The First Star-by-star N-body/Hydrodynamics Simulation of Our Galaxy Coupling with a Surrogate Model
Keiya Hirashima, Michiko S. Fujii, Takayuki R. Saitoh, Naoto Harada, Kentaro Nomura, Kohji Yoshikawa, Yutaka Hirai, Tetsuro Asano, Kana Moriwaki, Masaki Iwasawa, Takashi Okamoto, Junichiro Makino
计算天体物理学的一个主要目标是以足够高的分辨率模拟银河系，直至单个恒星级别。然而，由于某些小尺度、短时标现象（如超新星爆发）的存在，这种缩放难以实现。我们开发了一种结合机器学习的N体/流体动力学模拟新集成方案。该方法通过使用代理模型绕过了由超新星爆发引起的短时间步长问题，从而提高了可扩展性。利用这种方法，我们使用148,900个节点（相当于7,147,200个CPU核心）达到了3000亿个粒子，突破了当前最先进模拟面临的十亿粒子障碍。这一分辨率使我们能够执行首个逐星星系模拟，解析银河系中的单个恒星。该性能在超过10^4个CPU核心上实现可扩展，这是当前使用A64FX和X86-64处理器以及NVIDIA CUDA GPU的最先进模拟的上限。
A major goal of computational astrophysics is to simulate the Milky Way Galaxy with sufficient resolution down to individual stars. However, the scaling fails due to some small-scale, short-timescale phenomena, such as supernova explosions. We have developed a novel integration scheme of N-body/hydrodynamics simulations working with machine learning. This approach bypasses the short timesteps caused by supernova explosions using a surrogate model, thereby improving scalability. With this method,...
