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:开发复杂可靠的先进加速器需要一个协调的、可扩展的和全面的建模方法,从源头到束末期寿命。我们提出了在 Exascale 计算中将加速器建模软件扩展到符合当代科学驱动器要求的亮点。特别是,我们使用美国能源部 Exascale 计算项目 WarpX,在 Exaflop 超级计算机上进行了首次激光等离子体建模。利用 Exascale 的发展,新的 DOE SCIDAC-5 粒子加速器高级建模联盟(CAMPA)将以一种协调的方式推进数值算法,并加速社区建模代码:从束源、能量提升、输运、注入、存储到应用或交互。这种从始至终的建模将使得探索混合加速器成为可能,其中包括常规和先进元素,作为先进加速器建模的下一步。遵循开放的社区标准,我们种植了一个代码的开放生态系统,这些代码可以很容易地与彼此和机器学习框架结合使用,这些将涵盖未来混合式加速器设计的超快速到超精确建模,甚至可以实现虚拟测试台和加速器的双胞胎,可在操作中使用。