Quantum Dynamics at Scale: Ultrafast Control of Emergent Functional Materials

S. Tiwari, A. Krishnamoorthy, P. Rajak, Putt Sakdhnagool, Manaschai Kunaseth, F. Shimojo, S. Fukushima, A. Nakano, Ye Luo, R. Kalia, K. Nomura, P. Vashishta
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Abstract

Confluence of extreme-scale quantum dynamics simulations (i.e. quantum@scale) and cutting-edge x-ray free-electron laser experiments are revolutionizing materials science. An archetypal example is the exciting concept of using picosecond light pulses to control emergent material properties on demand in atomically-thin layered materials. This paper describes efforts to scale our quantum molecular dynamics engine toward the United States' first exaflop/s computer, under an Aurora Early Science Program project named "Metascalable layered material genome". Key algorithmic and computing techniques incorporated are: (1) globally-scalable and locally-fast solvers within a linear-scaling divide-conquer-recombine algorithmic framework; (2) algebraic 'BLASification' of computational kernels; and (3) data alignment and loop restructuring, along with register and cache blocking, for enhanced vectorization and efficient memory access. The resulting weak-scaling parallel efficiency was 0.93 on 131,072 Intel Xeon Phi cores for a 56.6 million atom (or 169 million valence-electron) system, whereas the various code transformations achieved 5-fold speedup. The optimized simulation engine allowed us for the first time to establish a significant effect of substrate on the dynamics of layered material upon electronic excitation.
尺度量子动力学:新兴功能材料的超快控制
极端尺度量子动力学模拟(即quantum@scale)和尖端x射线自由电子激光实验的融合正在彻底改变材料科学。一个典型的例子是使用皮秒光脉冲在原子薄层材料中根据需要控制紧急材料特性的令人兴奋的概念。本文描述了在极光早期科学计划项目“元可扩展分层材料基因组”下,将我们的量子分子动力学引擎扩展到美国第一台百亿亿次/秒计算机的努力。采用的关键算法和计算技术有:(1)在线性缩放的分割-征服-重组算法框架内的全局可扩展和局部快速求解器;(2)计算核的代数“BLASification”;(3)数据对齐和循环重组,以及寄存器和缓存阻塞,以增强向量化和有效的内存访问。在131,072个Intel Xeon Phi内核上,一个5660万个原子(或1.69亿个价电子)系统的弱缩放并行效率为0.93,而各种代码转换实现了5倍的加速。优化后的模拟引擎使我们首次建立了衬底对层状材料在电子激发下动力学的显著影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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