Developing complex, reliable advanced accelerators requires a coordinated, extensible, and comprehensive approach in modeling, from source to the end of beam lifetime. We present highlights in Exascale Computing to scale accelerator modeling software to the requirements set for contemporary science drivers. In particular, we present the first laser-plasma modeling on an exaflop supercomputer using the US DOE Exascale Computing Project WarpX. Leveraging developments for Exascale, the new DOE SCIDAC-5 Consortium for Advanced Modeling of Particle Accelerators (CAMPA) will advance numerical algorithms and accelerate community modeling codes in a cohesive manner: from beam source, over energy boost, transport, injection, storage, to application or interaction. Such start-to-end modeling will enable the exploration of hybrid accelerators, with conventional and advanced elements, as the next step for advanced accelerator modeling. Following open community standards, we seed an open ecosystem of codes that can be readily combined with each other and machine learning frameworks. These will cover ultrafast to ultraprecise modeling for future hybrid accelerator design, even enabling virtual test stands and twins of accelerators that can be used in operations.
翻译:开发复杂、可靠的高级加速器需要协调的、可扩展的、综合的建模方法,从源到束流寿命的全部过程都需要建模。我们介绍了 Exascale 计算在扩展加速器建模软件方面的亮点,以满足当代科学驱动力的要求。特别是,我们展示了使用美国 DOE Exascale 计算项目 WarpX 在 exaflop 超级计算机上进行的第一次激光等离子体建模。借助 Exascale 的发展,新的 DOE SCIDAC-5 粒子加速器高级建模协会(CAMPA)将以一种协调的方式推进数值算法,并加快社区建模代码的发展:从束源,经过能耗增强、传输、注入、存储,到应用或相互作用。这样的从头到尾的建模将使探索混合加速器成为可能,其中包含传统元素和先进元素,是高级加速器建模的下一步。按照开放的社区标准,我们构建了一个开放的代码生态系统,这些代码可以很容易地与彼此和机器学习框架相结合。这些将覆盖未来混合加速器设计的超快速和超精确建模,甚至能够实现虚拟试验台和加速器克隆,可用于运行。