关于现代异质超级计算机的结合集群理论
Hector H Corzo1, Andreas Erbs Hillers-Bendtsen2, Ashleigh Barnes1
1Oak Ridge National Laboratory, Oak Ridge, TN, United States.
Frontiers in chemistry
|June 30, 2023
概括
本研究介绍了对合集群 (CC) 理论的Divide-Expand-Consolidate (DEC) 方法,以解决大型化学系统中的计算挑战. 对CPS (D-3) 模型的新算法为计算分子性质提供了可扩展和快速的解决方案.
科学领域:
- 计算化学是一种计算化学.
- 量子化学是一种量子化学.
- 理论化学是一种理论化学.
背景情况:
- 在计算上阐明复杂的化学系统带来了重大挑战.
- 传统的ab-initio方法与大分子系统的扩展斗争.
研究的目的:
- 将Divide-Expand-Consolidate (DEC) 方法作为线性缩放,对结合集群 (CC) 理论进行大规模并行框架.
- 引入集群扰动理论和CPS (D-3) 模型,以解决计算可扩展性的局限性.
- 详细介绍CPS (D-3) 方法的新算法,这些算法利用并行处理来有效计算分子性质.
主要方法:
- 实施分割-扩展-整合 (DEC) 框架用于合集群 (CC) 理论.
- 集群扰动理论的应用,以解决DEC方法的局限性.
- 开发用于CPS (D-3) 模型的新算法,使用多个节点和图形处理单元来进行张量收缩.
主要成果:
- DEC框架证明了对大型化学系统的适用性,但具有固有的局限性.
- 由CC单次和双次激发产生的CPS (D-3) 模型有效计算激发能.
- 新的算法通过高效利用并行处理资源来加速计算.
结论:
- CPS (D-3) 模型提供了一个可扩展,快速和精确的方法来计算大型系统中的分子性质.
- 这种方法为复杂的化学研究提供了传统合集群模型的有效替代方案.
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